JP2008067259A - Image processing apparatus, image output device, image processing method, image processing program, and recording medium with the program recorded thereon - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus, image forming apparatus, image output device, image processing method, image processing program, and recording medium with the program thereon in which halftone processing improved in edge reproducibility can be performed at high speed. <P>SOLUTION: A halftone processing unit 320 comprises a basic cell setting section 321 for dividing an image region of input image data into basic cells each including a predetermined region; an edge discriminating section 323 for discriminating whether a basic cell includes an edge regarding a gradation value change or not; a small cell setting section 325 which successively takes pixels into each small cell until a gradation value total within the small cell reaches a predetermined target gradation value, and divides a basic cell discriminated to include an edge into small cells; and a gradation value imparting section 326 which imparts an output gradation value to a pixel based on a position of the center of gravity of the gradation value within the cell for each pixel group of the basic cell discriminated not to include an edge and the small cell. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an image processing apparatus that performs halftone processing, an image output apparatus, an image processing method, an image processing program, and a recording medium on which the program is recorded.

  2. Description of the Related Art Conventionally, in a printer or the like, a bitmap format input image data expressed by a multi-value gradation number for each pixel is converted into a network having a gradation number corresponding to a dot (for example, binary corresponding to the presence or absence of a dot). Printing is performed by converting to output image data expressed by dots and forming dots according to the output image data. At this time, the quantization processing for converting multi-value gradation data into halftone data is called halftone processing. Typical examples of halftone processing include a dither method and an error diffusion method.

  Also, as one method of halftone processing, the image area of the input image data is divided into pixel groups (hereinafter also referred to as “cells”) composed of a collection of a plurality of pixels, and the output gradation value for each cell. A method of imparting is also known.

  For example, in Patent Document 1, a cell having a predetermined shape is set in an image area of input image data, and the gradation value in the cell is summed in order from a pixel close to the gravity center position of the gradation value in the cell. A technique is disclosed in which dot size control is performed by assigning output gradation values to a corresponding number of pixels and forming dots in accordance with the output gradation values. A halftone processing method that performs dot position control based on the center of gravity in addition to dot size control is hereinafter referred to as “AAM method (Advanced AM method)”.

  Further, in Patent Document 2, pixels that are close to the centroid position of the in-cell tone value are successively taken in until the total tone value in the cell reaches a predetermined target tone value, and the cell is enlarged. A technique for giving an output gradation value to the position of the center of gravity is disclosed. If dots are formed according to this output gradation value, the cells are enlarged from the center of gravity to a substantially circular shape, and dots are formed at the center of gravity of the enlarged cells, thereby suppressing variations in inter-dot distance. Is possible. Therefore, it is possible to obtain an image with good dot dispersibility and excellent image quality. The halftone processing method at this time is hereinafter referred to as “CC method (Circular Cell method)”.

International Publication No. 2005/109851 Pamphlet Japanese Patent Laid-Open No. 2004-363639

  However, according to the AAM method described in Patent Document 1, since the cell shape is determined in advance and dots are formed at the center of gravity of the cell, the resolution at the time of image output is constant. For this reason, it is difficult to reproduce the edge portion where the gradation value changes rapidly with an appropriate resolution, and there is a problem that the reproducibility of the edge is lowered.

  In addition, according to the CC method described in Patent Document 2, the time required for processing becomes longer because the gradation value sum and the gravity center position are updated every time a new pixel is taken into the cell and the cell is enlarged. There is a problem of end.

  Accordingly, the present invention provides an image processing apparatus, an image output apparatus, an image processing method, an image processing program, and a recording medium on which the program is recorded, which can perform halftone processing with excellent edge reproducibility at high speed. With the goal.

  An image processing apparatus according to the present invention that achieves the above object is configured of a plurality of pixels, and input image data having a gradation value for each pixel is converted into two or more levels according to an output gradation value given to each pixel. Is a first pixel group setting unit that sets a plurality of first pixel groups by dividing an image area of input image data into predetermined areas. And an edge determination unit that determines whether or not the first pixel group includes an edge related to a gradation value change, and an image area of the first pixel group that is determined to include an edge, A second pixel group setting unit that sets the second pixel group, and a first pixel group and a second pixel group that are determined not to include an edge. A tone value that gives an output tone value to a pixel based on the barycentric position of the tone value Characterized in that it comprises a given unit.

  According to this configuration, the first pixel group of the predetermined area is set by dividing the image area of the input image data, and the first pixel group is set for the first pixel group that does not include the edge. An output gradation value is assigned to the pixel based on the barycentric position. On the other hand, the first pixel group including the edge is further divided to set a plurality of second pixel groups, and an output gradation value is given to the pixel based on the barycentric position of the second pixel group. Since the second pixel group is smaller than the first pixel group before partitioning, the distance between the pixels to which the output gradation value is given is reduced for the area including the edge in the image area of the input image data, Increases resolution. Therefore, output image data excellent in edge reproducibility can be obtained as compared with the technique described in Patent Document 1. In addition, since the first pixel group is set by dividing the image area that does not include the edge into a predetermined area, the amount of calculation required to set the first pixel group is small. . From the above, according to the present invention, halftone processing with excellent edge reproducibility can be performed at high speed.

  For example, if dots are formed according to the output gradation value using the output image data obtained by the image processing apparatus of the present invention, an image with excellent image quality can be output.

  Further, in the image processing device of the present invention, the second pixel group setting unit has a predetermined total tone value in the second pixel group in the image area of the first pixel group determined to include an edge. It is preferable to set the second pixel group by successively taking pixels into the second pixel group until the target gradation value is reached.

  According to this configuration, by taking in pixels for a predetermined target gradation value in the second pixel group, variation in the size of the second pixel group is suppressed, and a pixel to which an output gradation value is given. Variation in the distance between them is suppressed. Therefore, the dispersibility of the pixel position to which the output gradation value is given for the image area including the edge is improved, and halftone processing that is superior in edge reproducibility can be performed.

  The target gradation value is desirably set to a value corresponding to a dot size at which dot formation is easy to stabilize. In this way, dot formation is stable, and an image with superior gradation stability can be output.

  In the image processing apparatus of the present invention, the second pixel group setting unit is located at the center of gravity of the gradation value in the second pixel group, among the pixels that have not yet been captured into the second pixel group. It is preferable to capture near pixels.

  According to this configuration, since the second pixel group is likely to expand from the centroid position to a substantially circular shape by capturing pixels close to the centroid position of the gradation value in the second pixel group, the output Variation in distance between pixels to which gradation values are applied is suppressed. Therefore, it is possible to perform halftone processing that is more excellent in edge reproducibility.

  In the image processing device of the present invention, when the second pixel group setting unit captures a pixel in the second pixel group, the second pixel group in the first pixel group including the second pixel group. Among the pixels included in the first pixel group that have not been processed into the group and that have not been processed to give the output gradation value, the pixel that is closest to the gravity center position of the gradation value in the second pixel group Is preferably incorporated.

  According to this configuration, if the pixel is close to the position of the center of gravity, the pixels are also taken in from the adjacent first pixel group. Therefore, there is a possibility that the shape of the second pixel group may be biased particularly at the boundary portion between the first pixel groups. Becomes lower. As a result, the bias with respect to the position of the pixel to which the output gradation value is applied is suppressed, so that it is possible to perform halftone processing that is superior in edge reproducibility.

  In the image processing apparatus of the present invention, a highlight determination unit that determines whether or not the total tone value in the first pixel group is a highlight region that is smaller than a predetermined threshold, and a highlight region is determined. As for the first pixel group, the neighboring pixel groups are successively taken in until the total gradation value in the first pixel group reaches a predetermined target gradation value, and the first pixel group is expanded. It is preferable to further include an enlarged portion.

  According to this configuration, for the first pixel group determined to be the highlight area, the surrounding pixels are captured until the target gradation value is reached, and the first pixel group is enlarged, so that the target gradation An output gradation value corresponding to the value can be assigned. Accordingly, output image data having an output gradation value corresponding to the target gradation value can be obtained even in a highlight region having a small gradation value. According to this output image data, it is possible to output an image having excellent gradation stability in the highlight region.

  In the image processing apparatus of the present invention, when the pixel group enlargement unit captures a pixel in the first pixel group determined to be the highlight region, the pixel of the first pixel group adjacent to the first pixel group. Among them, it is preferable to capture the pixel closest to the center of gravity position of the gradation value in the first pixel group determined as the highlight region.

  According to this configuration, the first pixel group is enlarged from the centroid position to a substantially circular shape by taking in the pixels close to the centroid position of the gradation value in the first pixel group from the adjacent first pixel group. Therefore, in each first pixel group, the variation in the distance between the pixels to which the output gradation value is given is suppressed. Therefore, it is possible to perform halftone processing that is superior to the image quality in the highlight area.

  In the image processing apparatus according to the present invention, the gradation value assigning unit is configured to store a level in the pixel group for each of the first pixel group and the second pixel group determined not to include an edge. It is preferable to give an output gradation value corresponding to the total gradation value in the pixel group to the pixel based on the barycentric position of the tone value.

  According to this configuration, since the output gradation value corresponding to the total gradation value in the pixel group is given to the barycentric position of the pixel group, halftone processing with excellent gradation reproducibility of the input image data is performed. Can do.

  Further, in the image processing apparatus of the present invention, the gradation value assigning unit, when the sum of the gradation values in the pixel group exceeds the maximum output gradation value that can be assigned to one pixel, Preferably, output gradation values are assigned in order from pixels closer to the center of gravity of the tone value, and output gradation values corresponding to the total gradation value in the pixel group are assigned to the pixel group. .

  According to this configuration, even if the total tone value in the pixel group exceeds the maximum output tone value that can be given to one pixel, the pixels are output in order from the pixel closest to the center of gravity of the tone value in the pixel group. By assigning gradation values, output gradation values corresponding to the total gradation value of the input image data are assigned to the pixel group. Therefore, it is possible to perform halftone processing with excellent gradation reproducibility of input image data.

  Further, in the image processing apparatus of the present invention, the second pixel group setting unit does not capture the pixel having the maximum value that the gradation value of the input image data can take, without taking it into the second pixel group. The assigning unit preferably assigns the maximum output gradation value to the pixel having the maximum gradation value of the input image data.

  According to this configuration, for the pixel of the input image data having the maximum value, the maximum value is assigned to the output image data so that the gradation value of the maximum value is taken over. The maximum value of data is not converted to a value smaller than the maximum value of output image data. Therefore, it is possible to perform halftone processing with excellent reproducibility for the region having the maximum value in the input image data. For example, in the input image data, for a portion expressed by binary values such as text, dots are surely formed at the time of image output, so an image with excellent visibility for text such as characters should be output. Is possible.

  In the image processing apparatus of the present invention, the edge determination unit determines whether an edge is included based on a difference between the maximum value and the minimum value of the gradation values included in the first pixel group. Is preferred.

  According to this configuration, since it is possible to determine whether an edge is included or not by a simple process based on the difference between the maximum value and the minimum value of the gradation value, the halftone process with the edge determination is further performed. It can be done at high speed.

  Further, in the image processing device of the present invention, the second pixel group setting unit includes the first pixel group adjacent to each other for the pixel groups adjacent to each other among the first pixel groups determined to include the edge. For the image area combined, the pixels are successively taken into the second pixel group until the total gradation value in the second pixel group reaches the target gradation value, and the second pixel group is set. Is preferred.

  According to this configuration, for the pixel groups adjacent to each other among the first pixel groups determined to include the edge, the image area obtained by combining the first pixel groups adjacent to each other is divided into the second pixel groups. Thus, by giving an output gradation value to each second pixel group, halftone processing with excellent edge reproducibility can be performed at high speed.

  The image processing apparatus according to the present invention further includes a pulse width modulation unit capable of generating a pulse width signal for forming K (K is a positive integer) level dot for each pixel from the output image data. The tone value assigning unit generates enlargement direction information indicating a direction in which the set of pixels to which the output tone value is assigned is enlarged from the center of gravity position, and the pulse width modulation unit refers to the enlargement direction information, It is preferable to generate a pulse width signal starting from the position of the center of gravity in the pixel to which the tone value is given.

  According to this configuration, a newly generated pulse width signal is easily connected to a pulse width signal generated in an adjacent pixel. Therefore, when dots are formed according to the pulse width signal, there is a possibility that the dots are isolated. Lower. Accordingly, it is possible to obtain an image with more stable dot formation and improved gradation stability while improving gradation reproducibility with K-stage dots.

  According to another aspect of the present invention, a plurality of first pixels are formed by dividing an image area of input image data, which is configured by a large number of pixels and each pixel has a gradation value, into predetermined areas. A first pixel group setting unit that sets a group, an edge determination unit that determines whether or not the first pixel group includes an edge relating to a gradation value change, and a first pixel that is determined to include an edge A second pixel group setting unit for setting a plurality of second pixel groups by dividing an image area of the pixel group, and a first pixel group and a second pixel group determined not to include an edge For each pixel group, a tone value giving unit that gives an output tone value to a pixel based on the barycentric position of the tone value in the pixel group, and a dot is formed in the pixel to which the output tone value is given And an image output unit for outputting an image.

  According to this configuration, by performing halftone processing with excellent edge reproducibility at high speed and forming dots on pixels to which output gradation values have been assigned, images with excellent edge reproducibility can be generated at high speed. It becomes possible to output.

  The present invention may also be a method invention. That is, according to the image processing method of the present invention, input image data including a plurality of pixels and having a gradation value for each pixel is output with two or more kinds of levels represented by output gradation values given to each pixel. An image processing method for converting into image data, comprising: a first pixel group setting step of setting a plurality of first pixel groups by dividing an image area of input image data into predetermined areas; An edge determination step for determining whether or not one pixel group includes an edge relating to a gradation value change, and an image area of the first pixel group determined to include an edge is divided into a plurality of second regions. A second pixel group setting step for setting the pixel group, and a gradation value in the pixel group for each of the first pixel group and the second pixel group determined not to include an edge. With gradation value to give output gradation value to pixels based on the center of gravity position Characterized in that it comprises a step.

  Furthermore, the present invention may be a program or a recording medium storing the program. In other words, the image processing program of the present invention is configured to output two or more types of input image data composed of a large number of pixels and having gradation values for each pixel by output gradation values assigned to each pixel. An image processing program for converting to image data, wherein the computer reads out pattern data from a storage unit that stores in advance pattern data indicating an area to be set in a pixel group, and an image area of input image data according to the pattern data A first pixel group setting step for setting a plurality of first pixel groups by dividing each pixel into predetermined regions, and whether or not the first pixel group includes an edge relating to a gradation value change And a second pixel group setting step of setting a plurality of second pixel groups by partitioning an image region of the first pixel group determined to include an edge, A level for giving an output gradation value to a pixel based on the barycentric position of the gradation value in the pixel group for each of the first pixel group and the second pixel group determined not to include an edge. And a tone value assigning step. As a recording medium on which the program is recorded, various computer-readable media such as a flexible disk, a CD-ROM, a DVD-ROM, a magneto-optical disk, and a memory card can be used.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram illustrating a configuration of an image output system according to the first embodiment. As shown in FIG. 1, the image output system includes a host computer 10 that supplies input image data, and an image output device 20 that outputs an image according to the supplied input image data.

  The host computer 10 has an application unit 100 and a rasterizing unit 200.

  The application unit 100 generates data to be printed such as character data, graphic data, and bitmap data. The application unit 100 is, for example, a word processor or a graphic tool, and generates character data or graphic data by operating a keyboard or the like. The generated print target data is output to the rasterize unit 200.

  The rasterizing unit 200 converts (rasterizes) the data to be printed output from the application unit 100 into 8-bit bitmap image data for each pixel. The bitmap image data at this time is RGB data representing a color image by having gradation values (“0” to “255”) of RGB colors for each of a large number of pixels arranged in a matrix. The rasterized bitmap image data is output to the image output device 20 as input image data to the image output device 20.

  The image output device 20 is a laser printer that performs printing by electrophotographic image formation, and is roughly classified into image processing that performs various image processing on input image data supplied from the host computer 10 and converts it into output image data. And a print engine 400 that prints an image on a print medium such as paper according to output image data.

  The image processing unit 300 includes a color conversion unit 310, a halftone processing unit 320, and a pulse width modulation unit 330.

  The color conversion unit 310 performs a process of converting the input image data (RGB data) received from the host computer 10 into CMYK input image data.

  The halftone processing unit 320 performs halftone processing for converting the input image data (CMYK data) after color conversion into binary gradation values corresponding to the presence or absence of dots. The input image data is converted into output image data by halftone processing, and is output to the print engine 400. The halftone processing unit 320 is a characteristic part of the present invention, and detailed configuration / processing will be described later.

  The pulse width modulation unit 330 performs pulse width modulation on the output image data output from the halftone processing unit 320, thereby converting the presence / absence of dots to be formed in each pixel into drive data format data represented by a pulse width signal. . The pulse width modulation unit 330 outputs the output image data in the drive data format subjected to the pulse width modulation to the print engine 400.

  The print engine 400 includes a laser driver 410 and a laser diode 420. The laser driver 410 generates control data corresponding to the presence / absence of a drive pulse in accordance with the output image data output from the image processing unit 300, and drives the laser driver 410 with the control data so as to cover the surface of the photosensitive drum (not shown). Exposure. Then, an image obtained by developing the exposure image on the surface of the photosensitive drum is fixed on the surface of the printing paper by using a developing unit, an intermediate transfer member, a fixing unit (not shown), and the like. As a result, the image output apparatus 20 prints an image corresponding to the input image data.

  Next, the hardware configuration of the image output apparatus 20 will be described. As shown in FIG. 2, the image output apparatus 20 includes an input interface (hereinafter “input I / F”) 21, a CPU 22, a ROM (storage means) 23, a RAM 24, and a print engine 400. The components are connected to each other via a bus.

  The input I / F 21 is a part that receives input image data supplied from the host computer 10, and the input image data that has been input is temporarily stored in the RAM 24.

  The ROM 23 is a non-volatile memory such as a flash ROM or an EEPROM, and stores in advance an image processing program GP of the present invention, a cell pattern data CD of a cell repetition matrix (to be described later), a control program for the image output device 20, and the like. . In this embodiment, the image processing program GP is stored in the ROM 23 in advance. However, the image processing program GP may be supplied to the image output apparatus 20 in the form of a recording medium such as a memory card in which the image processing program GP is recorded.

  The RAM 24 is a memory mainly used as a working memory for various processes executed by the CPU 22, and stores an input buffer 24a for storing input image data after color conversion and output image data after halftone processing. Output buffer 24b is secured in a predetermined memory area.

  The CPU 22 controls each configuration of the input I / F 21, the ROM 23, the RAM 24, and the print engine 400 connected via the bus. In particular, the CPU 22 reads out the image processing program GP stored in the ROM 23 to the RAM 24 and executes the image processing program GP, thereby performing various processes as the image processing apparatus 300 such as color conversion, halftone processing, and pulse width modulation. I do.

  Next, the configuration of the halftone processing unit 320 which is a characteristic part of the present invention will be described. FIG. 3 is a block diagram showing the configuration of the halftone processing unit. As shown in FIG. 3, the halftone processing unit 320 includes a basic cell setting unit (first pixel group setting unit) 321, a highlight determination unit 322, an edge determination unit 323, and a basic cell enlargement unit (cell enlargement). Part) 324, a small cell setting part (second pixel group setting part) 325, and a gradation value giving part 326.

  The basic cell setting unit 321 is a part that divides the image area of the input image data into predetermined areas and sets cells. The cells set here are referred to as “basic cells (first pixel group)”.

  The basic cell setting unit 321 uses a cell repetition matrix in which a plurality of cells are laid out in a predetermined area in order to partition the area. FIG. 4 shows an example of the cell repetition matrix. As shown in FIG. 4, in the cell repetition matrix CM, a plurality of cells (cell numbers (1) to (8)) having the same size and shape are arranged in a staggered manner in a rectangular region. Here, the cells with cell numbers (3), (4), (6), (7), and (8) are each set to have a substantially circular shape. Cell numbers (1), (2), (5), etc., which are located around the matrix and are not substantially circular, are placed at adjacent positions when the cell repetition matrix CM is placed. The cells are set to be substantially circular basic cells when combined with the cells of the cell repetition matrix CM.

  The basic cell setting unit 321 arranges a cell repetition matrix CM for each area of the same size as the cell repetition matrix CM in the image area of the input image data, and divides the area for each cell of the cell repetition matrix CM. Thus, a plurality of basic cells having areas of a predetermined size and shape are set.

  For each of the basic cells, the highlight determination unit 322 determines whether the area in the cell is a highlight area that is output to a bright image with few dots generated when the image is output.

  The edge determination unit 323 determines, for each basic cell, whether or not the cell includes an edge relating to a change in the gradation value of the input image data (that is, a portion where the gradation value difference is abrupt). Based on this determination, a distinction is made between basic cells that contain edges and basic cells that do not contain edges.

  The basic cell enlarging unit 324 performs a process of enlarging the basic cell by successively taking pixels around the basic cell until the predetermined target gradation value is reached for the basic cell determined to be the highlight area. I do.

  This target gradation value is a value corresponding to the dot size that can be stably formed by the print engine 400, and depends on the resolution (dpi) set for the image output apparatus 20. Is determined. For example, if the resolution is 600 dpi, the target gradation value corresponding to the dot size of one pixel is “255”, and if the resolution is 1200 dpi, each dot becomes smaller and the dots are difficult to stabilize. “1275 (= 5 × 255)” corresponding to the dot size is set as the target gradation value. In the present embodiment, it is assumed that the target gradation value is set to “1275” in advance.

  The small cell setting unit 325 is a part that further divides an image area in a basic cell including an edge and sets a plurality of cells. The cell set here is referred to as a “small cell (second pixel group)”. The small cell setting unit 325 sets small cells by successively capturing pixels close to the barycentric position of the small cell gradation values until the total gradation value in the small cells reaches the target gradation value. As a result, the basic cell including the edge is further partitioned into a plurality of small cells each having a gradation value corresponding to the target gradation value in the cell.

  For each of the basic cell and the small cell that do not include an edge, the gradation value assigning unit 326 assigns an output gradation value corresponding to the total gradation value in the cell to the pixel based on the gravity center position of the in-cell gradation value. A process of giving (dot generation process) is performed. The output gradation value assigned here is a gradation value (“0” to “255”) expressed in 8 bits corresponding to the number of gradations of dots that can be formed by the print engine 400. For example, if the print engine 400 outputs an image by distinguishing the presence / absence of dots for each pixel, each pixel is output in advance to an output image area that is initially set to the output gradation value “0”. Thus, the output gradation value “255” is assigned to the pixel that generates the dot. As a result, output image data representing each pixel with two levels of output gradation values “0” or “255” is generated.

  As described above, the gradation value assigning unit 326 outputs to both the basic cell that does not include the edge and the small cell obtained by partitioning the basic cell, to the pixel based on the barycentric position in the cell. A gradation value is assigned. At this time, a series of processing for setting a basic cell by the cell repetition matrix CM and giving an output gradation value to the basic cell is in accordance with the processing method of the “AAM method”. A series of processing for dividing the basic cell into small cells and assigning output gradation values to the small cells follows the processing method of the “CC method”. Hereinafter, each processing method of the AAM method and the CC method will be briefly described.

  First, the AAM method will be described. The AAM method is a method of setting a basic cell having a predetermined region by arranging a cell repetition matrix CM and giving an output gradation value for each basic cell. FIG. 5 is a diagram for explaining basic cell setting by the cell repetition matrix CM, and shows an example in which a plurality of cell repetition matrices CM are arranged in the image area of the input image data. Here, the direction from left to right in the horizontal direction of the drawing is “x direction”, and the direction from top to bottom in the vertical direction of the drawing is “y direction”. Hereinafter, the x direction plus direction is also referred to as “right”, the x direction minus direction as “left”, the y direction plus direction as “down”, and the y direction minus direction as “up”.

  The basic cell is set by dividing the image area of the input image data into cell blocks CB having the same size as the cell repetition matrix CM, and arranging the cell repetition matrix CM for each cell block CB. Then, it is set in the basic cell CL1 corresponding to the cell set in the arranged cell repetition matrix CM. When setting the basic cell, as shown in FIG. 5, the cell blocks CB (a to a + 2, b to b + 1) are repeatedly set in the x direction and the y direction without any gaps, and each cell block CB is set. By arranging the cell repetition matrix CM, a plurality of basic cells CL1 are set.

  At this time, referring to FIG. 4, for cells (1), (2) and (5) which are not substantially circular in the periphery of the cell repetition matrix CM, the cell repetition matrix CM is arranged. In addition, when combined with the cells of the cell repetition matrix CM of the adjacent cell block CB, one basic cell CL1 having a substantially circular shape is obtained. For example, the cell (5) of the cell block CB (a + 1, b) is combined with the right end region of the cell block CB (a, b) to form a substantially circular basic cell CL1. Similarly, the cell (1) of the cell block CB (a + 1, b + 1) includes the lower right area of the cell block CB (a, b), the lower left area of the cell block CB (a + 1, b), the cell block CB ( Together with the upper right region of a, b + 1), a substantially circular basic cell CL1 is formed.

  Next, in the AAM method, dot generation processing for assigning an output gradation value for each basic cell CL1 is performed. 6A and 6B are diagrams for explaining dot generation processing. FIG. 6A is an example of a basic cell to be processed, and FIG. 6B is an example of a pixel to which an output gradation value is given in the cell. Show. In the example of FIG. 6A, the basic cell CL1 is composed of a region of gradation value “30” and a region of “50”, and the total gradation value in the cell is “3940 (= 255 × 15 + 115)”, The barycentric position G1 of the in-cell gradation value is (m + 5.48, n + 6.78).

  When the output gradation value is given, the output gradation value is given in order from the pixel close to the center of gravity position G, and the gradation value corresponding to the sum of the in-cell gradation values is given. Here, before the gradation value is given, the output gradation value “0” is initially set in the output buffer 24b, and the output gradation value to be given is the gradation value “255” corresponding to the presence of a dot. In the example of FIG. 6, the total tone value in the cell has a value that only gives the output tone value “255” to the 15 pixels, so 15 in the order closer to the centroid position G1. The output gradation value “255” is assigned to the pixels (see (1) to (15) in FIG. 6B) in order.

  Whether or not output gradation values corresponding to the remaining gradation values are to be assigned is determined by determining whether the remaining gradation values are equal to or greater than a predetermined threshold (for example, “127” which is half of the maximum value). To decide. In the example of FIG. 6, since the remaining gradation value “115” is less than the threshold value, the remaining gradation value “115” is not assigned to the 16th pixel.

  According to this AAM method, as shown in FIG. 6 (b), a substantially circular shape centered on the center of gravity position G1 of the basic cell CL1, and within a size range corresponding to the in-cell gradation value of the basic cell CL1. An output gradation value is given to the pixel.

  Next, the CC method will be described. FIG. 7 shows an example of the basic cell CL1 to be processed by the CC method. In the example of FIG. 7, the basic cell CL <b> 1 includes a region having a gradation value “50” and a region “200”.

  FIG. 8 is a diagram illustrating small cell setting performed by the CC method for the basic cell CL1 shown as an example in FIG. Hereinafter, it demonstrates in order according to FIG.

  In the CC method, first, an initial pixel serving as a starting point for generating the small cell CL2 is determined. The initial pixel is determined by searching, in raster order, an unprocessed pixel that has not been assigned an output gradation value using the gradation value in the pixel from the pixel in the basic cell CL1 according to a predetermined order. That is, scanning from the left end of the uppermost row of the target area to the right and searching to the right end, the next lower row is again searched in order from the left end to the right. The unprocessed pixel first found by the search is set as the initial pixel. In the example of FIG. 8A, when searching in the raster order, the unprocessed pixel (m + 6, n) is searched first from the basic cell CL1, and is thus taken into the small cell CL2 as an initial pixel. At this time, the gravity center position G2 of the gradation values in the small cell CL2 is (m + 6.00, n + 0.00), and the total gradation value in the small cell CL2 is “200”.

  Next, of the unprocessed pixels, the pixel closest to the gravity center position G2 is selected and taken into the cell. In the state of FIG. 8A, a pixel (m + 7, n + 1) whose distance from the gravity center position G2 is “1.41” and a pixel (m + 6, n + 1) whose distance from the gravity center position G2 is “1.00” And the pixel (m + 6, n + 1) having a shorter distance is taken into the small cell CL2 (see FIG. 8B). At this time, the center-of-gravity position G2 is updated to (m + 6.00, n + 0.50), and the total gradation value in the small cell CL2 is updated to “400”.

  Similarly, when the process of taking in pixels near the center of gravity G2 is repeatedly performed, the pixel (m + 7, n + 1), the pixel (m + 6, n + 2), the pixel (m + 7, n + 2), and the pixel (m + 5, n + 2) are sequentially displayed in the cell CL2. (See FIG. 8C). As a result, the gravity center position G2 is updated to (m + 6.17, n + 1.33), and the total gradation value in the small cell CL2 is updated to “1200”.

  Next, the pixel (m + 6, n + 3) is selected as the nearest unprocessed pixel from the gravity center position G2 (m + 6.17, n + 1.33), and is taken into the small cell CL2. Here, when all the gradation values of the pixels (m + 6, n + 3) are captured, the total gradation value in the small cell CL2 is “1400”, which exceeds the target gradation value “1275”. In such a case, the gradation value “125” exceeding the target gradation value is returned to the original pixel (m + 6, n + 3) (see FIG. 8D). In this way, a small cell CL2 having a gradation value corresponding to the target gradation value is set.

  Next, since unprocessed pixels that have not been captured in the small cell CL2 remain in the basic cell CL1, an initial pixel is set from the unprocessed pixels, and the same operation as that of the first small cell CL2 is performed. The second and subsequent small cells CL2 are set. At this time, the pixel of the gradation value returned to the original pixel in FIG. 8D is also processed as an unprocessed pixel. As described above, in the CC method, the process of setting the small cell CL2 having the gradation value for the target gradation value in the region in the basic cell CL1 is repeatedly performed so that the basic cell CL1 is a plurality of small cells CL2. Divide into

  In the CC method, when an output gradation value is given to the set small cell CL2, the same process as the dot generation process of the AAM method described in FIG. 6B is performed on the small cell CL2. . However, since the gradation value in the small cell CL2 is a predetermined target gradation value, the output gradation value is given to a predetermined number of pixels.

  According to the CC method, the basic cell CL1 is further divided into small cells CL2, and is substantially circular with the center of gravity G2 of the small cell CL2 as the center, and the output floor is within a range corresponding to the target gradation value. A key value is given. When dots are formed according to the output gradation value, dots are formed for each small cell CL2 obtained by dividing the basic cell CL1. Therefore, the CC method performed on the basic cell CL1 can be said to be a process in which the resolution of the image is higher than that of the AAM method.

  As described above, in the first embodiment, among the image areas of the input image, the image area that does not include the edge portion requires less number of updates of the centroid position / gradation value sum than the CC method. A halftone process is performed by applying the AAM method and applying the CC method having high resolution to the edge portion region.

  Next, the processing procedure of the halftone process according to the first embodiment will be described in detail with reference to the flowcharts of FIGS.

  The CPU 22 executes the image processing program GP read from the ROM 23, and converts the input image data received from the host computer 10 via the input I / F 21 into CMYK input image data. Then, the halftone process shown in FIGS. 9 and 10 is started for each color of C, M, Y, and K of the input image data.

  When the halftone process is started, the CPU 22 reads the input image data after color conversion, develops the input image in the input buffer 24a of the RAM 24 (step S100), and the cell block CB located at the upper left of the image area of the input image. A cell repetition matrix CM is set at (0, 0) (step S105). Here, attention is focused on one basic cell CL1 having the smallest cell number among the plurality of basic cells included in the set cell repetition matrix CM.

Next, the CPU 22 calculates the total tone value FT in the cell for the focused basic cell CL1 according to the following equation (step S110). However, “f” is a gradation value of a pixel in the basic cell, and “i” is a number corresponding to each pixel in the basic cell CL1.
FT = Σ _i f (i) (1)

  When the total gradation value is calculated, it is determined whether or not the total gradation value is equal to or greater than “0” (step S115). If the total gradation value is less than “0” (step S115: No), the process proceeds to step S155 without assigning the output gradation value to the basic cell CL1.

  If the total gradation value is “0” or more (step S115: Yes), the CPU 22 determines whether or not the focused basic cell CL1 is a highlight region (step S120). Specifically, it is determined whether or not the total gradation value in the basic cell CL1 is smaller than a predetermined threshold (> 0) corresponding to the boundary value between highlight and non-highlight. In step S120: Yes), it is determined that the area is a highlight area, and the process proceeds to step S145 to perform basic cell expansion processing. If it is equal to or greater than the threshold (step S120: No), it is determined that the area is a non-highlight area, and the process proceeds to step S125.

Hereinafter, the processing performed on the non-highlight area will be described. If it is determined in step S120 that it is a non-highlight area, the CPU 22 calculates the contrast of the gradation value in the noted basic cell CL1 (step S125). The contrast is calculated according to the following equation. That is, the difference value between the maximum value and the minimum value of the in-cell gradation values of the basic cell CL1 is set as the contrast C. However, max () is a function that returns the maximum value, and min () is a function that returns the minimum value.
C = | max (f (i)) − min (f (i)) | (2)

  Next, the contrast is compared with a predetermined reference value (for example, gradation value “80”, etc.) corresponding to the boundary value between the edge and the non-edge portion, and whether the focused basic cell CL1 includes an edge It is determined whether or not (step S130). If the contrast is equal to or higher than the reference value (step S130: Yes), it is determined that the noticed basic cell CL1 includes an edge, and the process proceeds to step S140 to perform the processing by the CC method for the noticed basic cell CL1. Do. If the contrast is less than the reference value (step S130: No), it is determined that the noticed basic cell CL1 does not include an edge, and the process proceeds to step S135, where the noticed basic cell CL1 is processed by the AAM method.

  Next, the processing procedure of the AAM method will be described with reference to the flowchart of FIG.

When the processing of the AAM method is started, first, the CPU 22 calculates the gravity center position G1 (G1x, G1y) of the in-cell gradation value of the noticed basic cell CL1 according to the following equation (step S200).
G1x = Σ _i x × f (i) (3)
G1y = Σ _i y × f (i) (4)

  Then, a dot generation process for assigning an output gradation value for generating dots to pixels near the center of gravity is performed (step S210). The dot generation process will be described with reference to the flowchart of FIG.

In the dot generation process, first, the CPU 22 determines a dot size to be output (step S300). In the AAM method, the dot size is determined from the sum of the in-cell tone values of the reference cell CL1 calculated in step S110 in order to form dots having a size corresponding to the sum of the in-cell tone values at the center of gravity position G1. In the present embodiment, by using the in-cell gradation value total FT, the gradation value of “127” or less is rounded down by the following formula, and the gradation value of “128” or more is scaled to “255” for one pixel. The dot size DS is determined by rounding up to the tone value. However, “int ()” is a function that truncates a fraction and returns an integer.
DS = n × 255
= Int (FT / 255 + 0.5) × 255 (5)

  When the dot size is determined, the CPU 22 calculates the distance between each non-output pixel that has not yet been assigned an output gradation value in the cell and the in-cell center of gravity position G1, and the closest to the in-cell center of gravity position G1. An output pixel is searched (step S310). Then, the output gradation value “255” is assigned to the searched pixel (step S320). Specifically, the output gradation value is given by adding the gradation value “255” to the value stored in the memory area of the output buffer 24b corresponding to the search pixel. If a plurality of non-output pixels closest to the in-cell center-of-gravity position G1 have been searched in step S310, an output gradation value is assigned to one randomly determined pixel among the plurality of search pixels. Good.

  Next, the CPU 22 determines whether or not the value after the output gradation value is given exceeds the maximum value “255” that the output gradation value can take (step S330). If it exceeds the maximum value (step S330: Yes), the output gradation value assigned to the pixel is adjusted to the maximum value “255” (step S340), and the process proceeds to step S350. If it does not exceed the maximum value (step S330: No), the process proceeds to step S350 without adjusting the output gradation value.

  Next, the CPU 22 determines whether or not the sum of the output gradation values assigned to the pixels in the cell has reached the gradation value for the dot size DS (step S350). If the gradation value for the dot size DS has been reached (step S350: Yes), the dot generation process ends.

  If the gradation value of the dot size DS has not been reached (step S350: No), output gradation values are assigned to all the pixels in the basic cell CL1, and it is determined whether or not all the pixels in the cell have been processed. (Step S360). If output gradation values are not assigned to all pixels (step S360: No), the process returns to step S310 to search for the next non-output pixel. If output gradation values have been assigned to all the pixels (step S360: Yes), the dot generation processing ends because there are no pixels to which output gradation values are to be assigned. When the dot generation process is completed, the AAM process ends, and the process returns to the processes of FIGS.

  If the contrast is larger than the reference value in step S130 in the flowchart of FIG. 9 (step S130: Yes), it is determined that the basic cell CL1 includes an edge with a large gradation value change, and step S140 is performed. Then, the processing by the CC method is performed for the basic cell CL1. Hereinafter, the processing procedure of the CC method for the basic cell will be described with reference to the flowchart of FIG.

  When the CC method processing for the basic cell CL1 is started, the CPU 22 determines whether or not there is an unprocessed pixel in the noticed basic cell CL1 (step S400). The pixels in the basic cell CL1 are searched in raster order, and when an unprocessed pixel is searched (step S400: Yes), the process proceeds to step S405 while paying attention to the searched unprocessed pixel. If there are no unprocessed pixels by performing the processing after step S405 (step S400: No), the CC method processing for the basic cell is terminated.

In step S405, the CPU 22 calculates the gravity center position G2 (G2x, G2y) of the gradation value in the small cell CL2 including the focused unprocessed pixel according to the following equation. However, “j” is a number corresponding to each pixel in the small cell CL2 on a one-to-one basis.
G2x = Σ _j x × f (j) (6)
G2y = Σ _j y × f (j) (7)

  Next, in step S410, the CPU 22 searches for an unprocessed pixel that is closest to the gravity center position G2 of the small cell CL2.

  In the search at this time, in addition to the unprocessed pixels in the basic cell CL1 to be processed, the center-of-gravity position G2 is selected from a plurality of unprocessed pixels obtained by further adding the unprocessed pixels of the adjacent basic cell CL1. Search for the pixel closest to. Thereby, the unprocessed pixel closest to the gravity center position G2 is searched without being bound by the division of the basic cell CL1.

  Next, in step S415, the CPU 22 determines whether or not the gradation value of the search pixel is the maximum value, that is, “255”. If it is the maximum value (step S415: Yes), the process proceeds to step S420 to search for the maximum output gradation value by writing the gradation value “255” in the area of the output buffer 24b corresponding to the search pixel. After giving to the pixel, the process returns to step S410.

  If the gradation value of the search pixel is not the maximum value (step S415: No), the process proceeds to step S425, and the value obtained by adding the gradation value of the search pixel to the total gradation value in the small cell CL2 is the target gradation value. It is determined whether or not: If it is below the target gradation value (step S425: Yes), the process proceeds to step S430, and the search pixel is taken into the small cell CL2. If the target gradation value is exceeded (step S425: No), the process proceeds to step S435, and only the insufficient gradation value from the target gradation value is taken into the small cell CL2, and the gradation value in the small cell is obtained. The total is adjusted to the target gradation value (see FIG. 8D).

  If the processing of step S430 or step S435 is performed, next, the new center of gravity position G2 and the gradation value total of the small cell CL2 are calculated and updated in consideration of the newly captured pixel (step S440).

  Next, it is determined whether or not the total gradation value in the small cell CL2 is equal to or greater than the target gradation value (step S445). If it is less than the target gradation value (step S445: No), the process proceeds to step S455 to determine whether there is an unprocessed pixel. If unprocessed pixels remain (step S455: Yes), the process returns to the process of step S410 to perform a process of searching for the next unprocessed pixel. If the total gradation value in the small cell CL2 is equal to or greater than the target gradation value (step S445: Yes), or if no unprocessed pixels remain (step S455: No), the process proceeds to step S450 to perform dot generation processing. Do.

  In the dot generation processing in the CC method, processing similar to the dot generation processing in the AAM method described in the flowchart of FIG. 12 is performed on the small cell CL2, but the processing in step S300 for determining the dot size is different. As described above, since a predetermined value (in this embodiment, “1275”) is used as the target gradation value of the CC method, the predetermined target gradation value is set to the dot size DS in step S300. The dot generation process is performed using this dot size DS. When the dot generation process in the CC method is completed, the process returns to FIG. 13 to determine whether or not unprocessed pixels remain (step S400). When the processing of steps S400 to S455 is repeated and there is no unprocessed pixel in the basic cell CL1 (step S400: No), the processing of the CC method for the basic cell is terminated, and the processing of FIGS. Return.

  The processing procedure of the basic cell enlargement process in step S145 performed when the basic cell CL1 is determined to be a highlight area in step S120 in FIG. 9 will be described with reference to the flowchart in FIG.

  When the basic cell enlargement process is started, first, the CPU 22 calculates the gravity center position G1 of the basic cell CL1 (step S500). And about the process of following step S510-S550, a new unprocessed pixel is made into a basic by performing the process similar to the process of step S410 and S425-S440 in CC method for object of a basic cell about basic cell CL1. The cell is expanded by taking in the cell CL1. Then, it is determined whether or not the total gradation value in the basic cell CL1 is equal to or greater than the target gradation value (step S560). If the target gradation value is not sufficient (step S560: No), it is determined whether or not unprocessed pixels remain (step S570). If unprocessed pixels remain (step S570: Yes), the process returns to step S510. If the in-cell tone value is equal to or higher than the target tone value (step S560: Yes) or if there is no unprocessed pixel in the basic cell CL1 (step S570: No), the basic cell enlargement process is terminated.

  When the basic cell enlargement process is completed, the process returns to the process of FIG. 9 to perform the dot generation process (step S150). Since the dot generation processing at this time is the same as that in step S450 in the CC method processing for basic cells, a description thereof will be omitted, but for the enlarged basic cell CL1, the cell center of gravity is determined in advance. The dot generation process is completed in a state where output gradation values corresponding to the target gradation values are given.

  In step S210, S450, or S150, when the output gradation value for the dot size is assigned and the dot generation process is completed, the CPU 22 then processes all the basic cells CL1 included in the set cell repetition matrix CM. Is determined (step S155). If all the basic cells CL1 have not been processed (step S155: No), after paying attention to the basic cell CL1 of the next cell number in the cell repetition matrix CM (step S160), the process returns to step S110, and the next Processing is performed on the basic cell CL1.

  If processing has been performed for all the basic cells CL1 included in the set cell repetition matrix CM (step S155: Yes), the process proceeds to step S165, and the CPU 22 sets the image area of the input image data. It is determined whether there is an unprocessed pixel on the right side of the cell repetition matrix CM, that is, in the x direction. If there is an unprocessed pixel on the right side (step S165: Yes), the cell repetition matrix CM is set so that the cell repetition matrix CM is arranged in the right cell block (step S170). And the process after step S110 is performed about the basic cell CL1 in the newly arranged cell repetition matrix CM. If there is no unprocessed pixel on the right side (step S165: No), it is determined whether there is an unprocessed pixel below the set cell repetition matrix CM, that is, in the y direction (step S175). If there is an unprocessed pixel on the lower side (step S175: Yes), the cell repetition matrix CM is arranged in the leftmost cell block on the lower side by one cell block (step S180) and newly arranged. For the basic cell CL1 in the cell repetition matrix CM, the processing after step S110 is performed. In this way, the arrangement of the cell repetition matrix CM is repeated in the raster order, and when there are no unprocessed pixels on the lower side (step S175: No), the halftone process of FIGS.

  By performing the halftone processing of FIGS. 9 and 10 described above, “0” or “255” is output for each pixel from the input image data after color conversion stored in the input buffer 24a onto the output buffer 24b. Output image data having gradation values is generated. This halftone process is performed for each color of C, M, Y, and K of the input image data. The halftone processing unit 320 reads out the generated C, M, Y, and K output image data from the output buffer 24 b and outputs them to the pulse width modulation unit 330. The pulse width modulation unit 330 performs pulse width modulation on the output image data, converts the output image data into output image data in a drive data format, and outputs the output image data to the print engine 400. The laser driver 410 of the print engine 400 drives the laser diode 420 according to the output image data in the drive data format, and forms dots on the pixels to which the output gradation value is given, thereby forming C, M, Y, A color image corresponding to the input image data is output by superimposing the K images.

  FIG. 15 shows an example of a cell set in the halftone process of this embodiment. FIG. 15A shows an example of an image area partitioned into basic cells CL1, and FIG. 15B shows an example where the basic cell shown in FIG. 15A is partitioned into small cells CL2. In FIG. 15A, the cell repetition matrix CM is arranged, and the basic cell CL1 that does not include the edge E as a part is indicated by a solid line, and the basic cell CL1 that includes the edge E as a part is indicated by a broken line. In the example of FIG. 15A, the left side from the edge E is a region with a high gradation value (“200”), and the right side is a region with a small gradation value (“50”). A halftone process by the AAM method is performed on the basic cell CL1 which does not include the edge E in part. On the other hand, with respect to the basic cell CL1 including even the edge E as a part, as shown in FIG. 15B, one basic cell CL1 is partitioned into a plurality of small cells CL2 by the process of the CC method.

  In step S410, the boundary portion of the basic cell CL1 including the edge E is obtained by searching for the nearest pixel from the unprocessed pixels of the basic cell CL1 to be processed and the unprocessed pixels of the adjacent basic cell CL1. , The setting of the small cell CL2 that spans the adjacent basic cell CL1 is allowed (see, for example, the small cell A in FIG. 15B). Thereby, even if it is small cell CL2 set to the boundary part between basic cells CL1, generation | occurrence | production of the deviation of a cell shape is suppressed and it becomes a substantially circular shape.

  Hereinafter, effects in the first embodiment will be described.

  (1) The basic cell CL1 determined not to include an edge is partitioned into predetermined areas using the cell repetition matrix CM, and the basic cell CL1 is set. Therefore, it is necessary to set the basic cell CL1. The amount of calculation is small. In particular, compared with the case where the basic cell CL1 is set using the CC method, the amount of calculation required for the calculation of the sum of gradation values, the update of the center of gravity position, etc. is reduced. Further, the basic cell CL1 determined to include an edge is further divided into small cells CL2 by the CC method, and an output gradation value is given to the center of gravity position G2 of the small cell CL2. Increases nature. Therefore, halftone processing with excellent edge reproducibility can be performed at high speed. Further, by forming dots according to the output gradation value of the generated output image data, it is possible to output an image with excellent edge reproducibility at high speed.

  (2) In the AAM method performed on the basic cell CL1 determined not to include an edge, the cell shape is larger than the CC method performed on the basic cell CL1, and thus the sum of in-cell gradation values is also large. The number of pixels to which output gradation values are assigned tends to increase. For this reason, the dot size formed in one cell increases, and unstable dot formation due to exposure, development, and fixing of small dots is suppressed, so dot formation is more stable. Therefore, it is possible to output an image that is superior in gradation stability for a region that does not include an edge.

  (3) In the CC method performed on the basic cell CL1 determined to include an edge, the pixels are divided into small cells CL2 so that pixels are successively taken in until the target gradation value is reached. The variation in the distance is suppressed, and the variation in the distance between the pixels to which the output gradation value is given is suppressed. Therefore, it is possible to output an image with excellent image quality by performing halftone processing with excellent dispersibility of pixel positions to which output gradation values are assigned. In addition, the target gradation value corresponds to the dot size where dots are stably formed according to the set resolution. Therefore, stable dot formation while increasing dot resolution provides excellent gradation stability. An image can be output.

  (4) In the CC method, since the small cells CL2 are enlarged in order from the pixels close to the in-cell center of gravity position G2, the small cells CL2 are highly likely to expand into a substantially circular shape with the center of gravity position G2 as the center. This suppresses variations in the distance between pixels to which output gradation values are assigned between the small cells CL2, so that halftone processing with excellent dispersion of pixel positions to which output gradation values are assigned is performed. It is possible to output an image with excellent image quality.

  (5) When assigning output gradation values in the dot generation process, the output gradation values “255” are assigned in order from the pixels closer to the center of gravity in the sum of the in-cell gradation values for the target gradation values. Therefore, the generated dots expand from the center of gravity position to a substantially circular shape. Accordingly, it is possible to perform a halftone process that is superior in the dispersibility of the pixel position to which the output gradation value is given, and to output an image that is superior in image quality. Further, since the number of pixels (dot size) to which the output gradation value is given is determined according to the total gradation value in the cell, an image with excellent gradation reproducibility of the input image data can be output. .

  (6) Among the basic cells CL1, for the basic cell CL1 determined to be the highlight region, the pixels near the barycentric position G1 of the in-cell gradation value are taken from the adjacent basic cell CL1 to expand the cell. The total tone value in the cell reaches the target tone value (step S145: basic cell enlargement process). Thereby, even in a highlight area where the number of pixels in which dots are generated is small, a dot having a size corresponding to the target gradation value (a size corresponding to five pixels in the present embodiment) is generated. Generated. Therefore, an image having excellent gradation stability in the highlight region can be obtained. In the cell enlargement process, since the basic cell CL1 is enlarged in a substantially circular shape in order from the pixels close to the center of gravity, an image with excellent image quality can be output even in the highlight area.

  (7) Edge determination is performed by calculating contrast, which is a difference value between the maximum value and the minimum value of the gradation values in the basic cell CL1, and determining whether the contrast exceeds a predetermined reference value. (Steps S120 and S130). Therefore, the edge determination can be determined by a simple process with a small calculation amount, and the halftone process with the edge determination can be performed at a higher speed.

  (8) When searching for unprocessed pixels to be newly taken into the small cell CL2 (step S410), in addition to the unprocessed pixels of the basic cell CL1 to be processed, the unprocessed pixels of the adjacent basic cell CL1 are further added. Since the pixel closest to the center-of-gravity position G2 is searched from among the plurality of unprocessed pixels, the possibility that the shape of the small cell CL2 set in the boundary portion between the basic cells CL1 is biased is low, and is substantially circular. Approach the shape. For this reason, it is possible to output an image with higher image quality by performing halftone processing with small dot position deviation and excellent dispersibility of pixel positions to which output gradation values are applied.

(Second Embodiment)
Next, a second embodiment of the present invention will be described.

  In the second embodiment, for the basic cell CL1 determined to include an edge, the small cell CL2 is set by the CC method without being constrained by the area of the basic cell CL1. That is, the halftone process by the CC method is applied to a region where the regions of the basic cells CL1 adjacent to each other among the basic cells CL1 determined to include an edge are combined. Hereinafter, halftone processing according to the second embodiment will be described with reference to the flowcharts of FIGS. Note that the description of the part that performs the same processing as in the first embodiment is omitted.

  Since the halftone process is started and the processes in steps S600 to S625 are the same as the processes in steps S100 to S125 in the first embodiment, the description thereof is omitted.

  When the process proceeds from step S625 to step S630, the CPU (edge determination unit 323) 22 determines whether or not the basic cell CL1 includes an edge. If it is determined that the basic cell CL1 does not include an edge (step S630: No), the process proceeds to step S635, and the same processing as the AAM method described in the first embodiment is performed. On the other hand, if it is determined that the basic cell CL1 includes an edge (step S630: Yes), unlike the first embodiment, the process proceeds to step S655 without performing the CC method for the basic cell. Regarding the processing of the next steps S655 to S680, the same processing as that of steps S155 to S180 in the first embodiment is performed, and thus the description thereof is omitted.

  However, if it is determined in step S675 that there is no unprocessed pixel below the set cell repetition matrix CM (step S675: No), the process proceeds to step S685. At this time, in the image area of the input image data, the output gradation value by the AAM method is given to the area of the basic cell CL1 not including the edge, and the area of the basic cell CL1 including the edge remains in the unprocessed pixel state. It has become. In step S685, the CC method (CC method for all unprocessed pixels) is performed on all regions where the unprocessed pixels remain. Hereinafter, description will be made with reference to the flowchart of FIG.

  When the CC method for all unprocessed pixels is started, it is determined whether or not unprocessed pixels remain in all image regions of the input image data (step S700). If unprocessed pixels remain (step S700: Yes), search is performed in raster order, the unprocessed pixels searched first are taken as initial pixels in the small cell CL2, and then the position of the center of gravity in the small cell CL2 is calculated. (Step S705).

  The processes in steps S710 to S755 are performed in the same manner as steps S405 to S455 in the first embodiment, and the processes in steps S700 to S750 are repeated until there are no unprocessed pixels in the image area of the input image data. When there are no unprocessed pixels, the CC method for all unprocessed pixels in FIG. 18 and the halftone processes in FIGS.

  According to the halftone processing described above, the basic cell CL1 determined not to include an edge is processed by the AAM method, and the remaining image region (that is, the basic cell CL1 determined to include an edge) is processed. In the case of (region), all the unprocessed pixels are processed by the CC method without being bound by the division of the basic cell CL1. As a result, for a basic cell CL1 that does not include the edge E (see the solid line basic cell in FIG. 15A), a halftone process is performed by the AAM method, and a basic cell that includes the edge E as a part thereof. For the region (see the broken line basic cell in FIG. 15A), halftone processing by the CC method is performed.

  According to the second embodiment, the same effects as (1) to (7) in the first embodiment can be obtained.

(Third embodiment)
Next, a third embodiment of the present invention will be described.

  The pulse width modulation unit 330 according to the third embodiment performs pulse width modulation on the output image data output from the halftone processing unit 320 to thereby generate a pulse having a pulse width of 2 or more K (K is an integer). It can be converted to a width signal. In the present embodiment, a case will be described in which the pulse width modulation unit 330 corresponds to a 255-level pulse width signal.

  In the first embodiment, as described in Expression (5), the gradation value equal to or smaller than “127” is rounded down, and the dot corresponding to “255” is generated for the gradation value larger than “127”. It was. For this reason, in the example of FIG. 6, the gradation value “255” is assigned to 15 pixels, and the output gradation value is not assigned to the remaining gradation value “115”.

  On the other hand, in the third embodiment, the pulse width modulation unit 330 can generate a 255-level pulse width signal. Therefore, in the case of the example of FIG. The remaining gradation value “115” is assigned to the pixel (m + 6, n + 9) close to the gravity center position G1.

  Therefore, when generating the output image data, the tone value assigning unit 326 assigns the output tone value to the pixels to which the output tone value has been assigned one after another, so that the set of assigned pixels becomes the center of gravity position. Generate dot growth data (enlargement direction information) indicating the direction of enlargement from G1, that is, the dot growth direction.

  The pulse width modulation unit 330 refers to the dot growth data when assigning an output gradation value less than the gradation value “255”, and in the pixel to which the output gradation value is to be applied, it is opposite to the dot growth direction. A pulse width signal corresponding to the output gradation value is generated starting from the side, that is, the side closer to the center of gravity.

  When this pulse width modulation is performed in the example of FIG. 6, as shown in FIG. 19, the pixel (m + 6, n + 9) has a pulse width corresponding to the output gradation value “115” from the left side of the pixel. Dots are formed. By doing so, one block-like dot is generated in the basic cell CL1, and dot isolation is suppressed.

  According to the third embodiment, in addition to (1) to (7) in the first embodiment, the following effects can be further obtained.

  (9) In the AAM method, by adding the target gradation values corresponding to the gradation values in the basic cell CL1, the sum of the gradation values in the cell before and after the halftone processing and the sum of the output gradation values are Therefore, it is possible to perform halftone processing that is superior in tone reproducibility of input image data.

  (10) By suppressing the isolation of dots, dot formation is more stable, and an image superior in gradation stability can be output.

  The first to third embodiments of the present invention have been described above. However, the present invention is not limited to this, and various forms can be adopted. Hereinafter, modifications of the present invention will be described.

  (Modification 1) In the first to third embodiments, the edge is determined by using the difference value between the maximum value and the minimum value of the gradation value of the CL1 in the basic cell. Not limited to. For example, the edge may be detected by detecting an edge using an edge detection filter such as Sobel or Prewitt, and whether the edge is included in the basic cell CL1. In addition, when rasterizing print data described in a printer language such as PDL (Page Description Language), additional information indicating the drawing range of the text portion is added to the input image data, and the additional information is referred to in halftone processing. Then, the basic cell CL1 including the text drawing range may be determined as the basic cell CL1 including the edge. In this way, it is possible to output an image with good visibility for the text portion.

  (Modification 2) As a second modification, the present invention may have a system configuration in which halftone processing is performed on the host computer 10 side. That is, as shown in FIG. 20, the host computer (image processing apparatus) 10 includes an image processing unit 300 including a rasterizing unit 200, a color conversion unit 310, and a halftone processing unit 320. At this time, the halftone processing unit 320 performs halftone processing on the input image data to convert it to output image data, and outputs the output image data after color conversion to the image output device 20, thereby printing the input image data. I do.

  (Modification 3) In the first to third embodiments, the case where the basic cell CL1 including the edge is divided into the small cells CL2 using the CC method has been described, but also when dividing into the small cells CL2, You may divide into the cell shape decided beforehand. That is, cell pattern data for partitioning the basic cell CL1 into a plurality of small cells CL2 is stored in the ROM 23 in advance, and the cell pattern is arranged for the basic cell CL1 determined to include an edge. To divide into small cells CL2. Even in this case, since the resolution of the edge portion can be improved, halftone processing excellent in edge reproducibility can be performed at high speed.

  (Modification 4) Regarding the cell repetition matrix CM, the shape and size of the generated basic cell CL1 are not limited to the example of FIG. For example, the shape of the basic cells may be a square shape, or a matrix in which the basic cells CL1 having a hexagonal shape are arranged in a honeycomb shape. Different matrices may be applied to C, M, Y, and K colors. In the example of FIG. 4, the basic cells are arranged along the x and y directions. However, for example, if a mat risk in which the basic cells are arranged in a direction shifted by 30 ° is applied between the colors, each color is applied. It is possible to obtain a suitable image with little variation in dot positions between them and less moire.

  (Modification 5) In the first to third embodiments, an example has been described in which the CPU 22 executes the image processing program GP to realize halftone processing by software. The function of performing halftone processing may be realized by hardware such as ASIC. Of course, a part of the functions may be given to the hardware, and the functions that the hardware does not have may be realized by software.

  (Modification 6) In the first to third embodiments, the image output apparatus as the image processing apparatus is a laser printer. The present invention is not limited to this, and can be applied to various devices such as printers, copiers, word processors, fax machines, displays, and the like of other printing systems such as inkjet printers and thermal printers.

The figure which showed the structure of the image output system which concerns on 1st Embodiment. The figure which showed the hardware constitutions of the image output device. The block diagram which showed the structure of the halftone process part. The figure which showed an example of the cell repetition matrix. The figure for demonstrating the basic cell setting by a cell repetition matrix. It is a figure for demonstrating a dot production | generation process, (a) is an example of a basic cell, (b) is a figure which showed an example which provided the output gradation value. The figure which showed an example of the basic cell made into the processing object of CC method. The figure for demonstrating the small cell setting performed by CC method. The flowchart which showed the process sequence of the halftone process. The flowchart which showed the process sequence of the halftone process. The flowchart which showed the process sequence of the process of AAM method. The flowchart which showed the process sequence of the dot production | generation process. The flowchart which showed the flow of the process of CC method targeting the basic cell. The flowchart which showed the process sequence of the basic cell expansion process. The figure which showed an example of the cell setting. 10 is a flowchart showing a processing procedure of halftone processing according to the second embodiment. The flowchart which showed the process sequence of the halftone process. The flowchart which showed the processing procedure of CC method for all the unprocessed pixels. The figure which showed an example of the dot output in 3rd Embodiment. The figure for demonstrating a 2nd modification.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 ... Host computer, 20 ... Image output device, 21 ... Input interface, 22 ... CPU, 23 ... ROM as storage means, 24 ... RAM, 24a ... Input buffer, 24b ... Output buffer, 100 ... Application part, 200 ... Rasterization 300, an image processing unit as an image processing apparatus, 310, a color conversion unit, 320, a halftone processing unit, 321, a basic cell setting unit as a first pixel group setting unit, 322, a highlight determination unit, 323. ... edge determination unit, 324 ... basic cell enlargement unit as pixel group enlargement unit, 325 ... small cell setting unit as second pixel group setting unit, 326 ... gradation value giving unit, 330 ... pulse width modulation unit, 400 ... print engine as image output unit, 410 ... laser driver, 420 ... laser diode, CD ... as pattern data Cell pattern data, GP ... image processing program, CM ... cell repetition matrix, CL1 ... basic cells, CL2 ... small cells, CB ... cell block, the center of gravity of the G1 ... basic cell, the center of gravity of the G2 ... small cells.

Claims (16)

An image processing apparatus that converts input image data composed of a large number of pixels and having gradation values for each pixel into output image data that represents two or more levels by output gradation values assigned to each pixel. And
A first pixel group setting unit that divides an image area of the input image data into predetermined areas and sets a plurality of first pixel groups;
An edge determination unit for determining whether or not the first pixel group includes an edge related to a gradation value change;
A second pixel group setting unit that sets an image area of the first pixel group determined to include the edge and sets a plurality of second pixel groups;
For each pixel group of the first pixel group and the second pixel group determined not to include the edge, the output gradation value is applied to a pixel based on the barycentric position of the gradation value in the pixel group. An image processing apparatus comprising: a gradation value providing unit that provides The image processing apparatus according to claim 1.
The second pixel group setting unit, until the total tone value in the second pixel group reaches a predetermined target tone value in the image region of the first pixel group determined to include the edge An image processing apparatus, wherein pixels are successively taken into the second pixel group to set the second pixel group. The image processing apparatus according to claim 2,
The second pixel group setting unit captures a pixel that is closest to the gravity center position of the gradation value in the second pixel group among pixels that have not yet been captured into the second pixel group. An image processing apparatus. The image processing apparatus according to claim 3.
When the second pixel group setting unit captures a pixel into the second pixel group, the capture into the second pixel group in the first pixel group including the second pixel group is not processed. And the pixel closest to the barycentric position of the gradation value in the second pixel group among the pixels included in the first pixel group in which the output gradation value is not yet processed is fetched. An image processing apparatus. In the image processing device according to any one of claims 1 to 4,
A highlight determination unit that determines whether or not the total gradation value in the first pixel group is a highlight region smaller than a predetermined threshold;
For the first pixel group determined to be the highlight region, the surrounding pixels are successively taken in until the total gradation value in the first pixel group reaches a predetermined target gradation value, and the first pixel group And a pixel group enlargement unit for enlarging the pixel group. The image processing apparatus according to claim 5.
When the pixel group expansion unit captures a pixel in the first pixel group determined as the highlight area, the highlight area among the pixels of the first pixel group adjacent to the first pixel group An image processing apparatus that captures a pixel that is closest to the barycentric position of the gradation value in the first pixel group determined as. The image processing apparatus according to any one of claims 1 to 6,
The gradation value providing unit is configured to set the gradation value in the pixel group at the center of gravity for each pixel group of the first pixel group and the second pixel group determined not to include the edge. An image processing apparatus, wherein an output gradation value corresponding to a total gradation value in the pixel group is assigned to a pixel based on the pixel. The image processing apparatus according to claim 7.
When the total tone value in the pixel group exceeds the maximum output tone value that can be given to one pixel, the tone value assigning unit is a pixel close to the center of gravity of the tone value in the pixel group An image processing apparatus characterized in that output gradation values are assigned to the pixel group corresponding to the total gradation value in the pixel group so that output gradation values are assigned in order. The image processing apparatus according to any one of claims 1 to 8,
The second pixel group setting unit does not capture the pixel having the maximum value that can be taken by the gradation value of the input image data into the second pixel group,
The image processing apparatus, wherein the gradation value providing unit assigns the maximum value of the output gradation value to a pixel having the maximum gradation value of the input image data. The image processing apparatus according to any one of claims 1 to 9,
The image processing apparatus according to claim 1, wherein the edge determination unit determines whether an edge is included based on a difference between a maximum value and a minimum value of gradation values included in the first pixel group. The image processing device according to any one of claims 1 to 10,
The second pixel group setting unit, for the pixel groups adjacent to each other among the first pixel groups determined to include the edge, for an image region obtained by combining the first pixel groups adjacent to each other The second pixel group is set by successively taking pixels into the second pixel group until the total gradation value in the second pixel group reaches the target gradation value. An image processing apparatus. The image processing apparatus according to claim 8.
A pulse width modulation unit capable of generating a pulse width signal for forming K-stage dots (K is a positive integer) for each pixel from the output image data;
The gradation value giving unit generates enlargement direction information indicating a direction in which a set of pixels to which the output gradation value is given is enlarged from the center of gravity position,
The image processing characterized in that the pulse width modulation unit generates the pulse width signal starting from the barycentric position side in a pixel to which the output gradation value is given with reference to the enlargement direction information apparatus. A first pixel group setting unit configured to set a plurality of first pixel groups by dividing an image area of input image data including a plurality of pixels and having gradation values in each pixel for each predetermined area When,
An edge determination unit for determining whether or not the first pixel group includes an edge related to a gradation value change;
A second pixel group setting unit that sets an image area of the first pixel group determined to include the edge and sets a plurality of second pixel groups;
For each pixel group of the first pixel group and the second pixel group determined not to include the edge, the output gradation value is applied to a pixel based on the barycentric position of the gradation value in the pixel group. A gradation value providing unit for providing
An image output apparatus comprising: an image output unit configured to output an image by forming dots at pixels to which the output gradation value is assigned. An image processing method for converting input image data composed of a large number of pixels and having a gradation value to each pixel into output image data representing two or more levels by an output gradation value assigned to each pixel. And
A first pixel group setting step of setting a plurality of first pixel groups by dividing an image area of the input image data into predetermined areas;
An edge determination step of determining whether or not the first pixel group includes an edge related to a gradation value change;
A second pixel group setting step of setting a plurality of second pixel groups by partitioning an image region of the first pixel group determined to include the edge;
For each pixel group of the first pixel group and the second pixel group determined not to include the edge, the output gradation value is applied to a pixel based on the barycentric position of the gradation value in the pixel group. An image processing method comprising: a gradation value assigning step for assigning. An image processing program for converting input image data composed of a large number of pixels and having gradation values to each pixel into output image data representing two or more levels by output gradation values assigned to each pixel Because
On the computer,
The pattern data is read from a storage unit that prestores pattern data indicating an area to be set in the pixel group, and an image area of the input image data is divided into predetermined areas in accordance with the pattern data, and a plurality of areas are defined. A first pixel group setting step for setting a first pixel group;
An edge determination step of determining whether or not the first pixel group includes an edge related to a gradation value change;
A second pixel group setting step of setting a plurality of second pixel groups by partitioning an image region of the first pixel group determined to include an edge;
For each pixel group of the first pixel group and the second pixel group determined not to include the edge, the output gradation value is applied to a pixel based on the barycentric position of the gradation value in the pixel group. An image processing program that executes a gradation value assigning step for assigning.   A computer-readable recording medium on which the image processing program according to claim 15 is recorded.

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