CN111292246B - Image color correction method, storage medium, and endoscope - Google Patents
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Abstract
An image color correction method, a storage medium, and an endoscope, the image color correction method including: shooting a standard color card by using a system to be corrected to obtain values to be corrected of R, G, B of n color blocks in the color card and values to be corrected of components L, M, N of a color model; establishing an inequality constraint function; correcting the to-be-corrected numerical values R, G, B of n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix; obtaining the component values L of the converted color model 1 、M 1 、N 1 The method comprises the steps of carrying out a first treatment on the surface of the Standard value L of each component according to color model in standard color card b 、M b 、N b And component values L of the converted color model 1 、M 1 、N 1 Establishing an objective function; and fitting the objective function according to the constraint function and the objective function under the condition that the value of the objective function is minimum, and obtaining a color correction matrix coefficient X. The method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual needs.
Description
Technical Field
The present invention relates to the field of image processing, and in particular, to an image color correction method, a storage medium, and an endoscope.
Background
With the development of computer science and color input and output technology, color images are used as information carriers and are increasingly widely applied to various fields such as printing, film and television, advertisement, electronic commerce, digital entertainment and the like, and the requirements of people on color reproduction quality are also higher. However, in the process of acquiring a color image by an imaging system such as a camera, a certain deviation occurs between the color of the captured image and the color of the real object, and in order to reduce the deviation, the color correction is generally performed on the image captured by the image capturing apparatus.
In the method of image color correction, the most basic RGB (red, green and blue) color space is generally converted into other color spaces suitable for computational adjustment, such as HSI (hue, saturation and intensity) color space, HSV (hue, saturation and brightness), YUV (brightness, chroma and density) color space, lab color space, and the like, and then the adjustment is performed. However, the process of the adjustment method is complicated, and complicated image data analysis is required.
Disclosure of Invention
The invention aims to provide an image color correction method, a storage medium and an endoscope. The image color correction method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual requirements.
The embodiment of the invention provides an image color correction method, which comprises the following steps:
s1: shooting a standard color card by using a system to be corrected to obtain values to be corrected of R, G, B of n color blocks in the color card and values to be corrected of components L, M, N of a color model;
s2: establishing an inequality constraint function: and A is X-B is less than or equal to K, wherein,r, G, B is the value to be corrected of n color blocks in the standard color card; />R b 、G b 、B b The standard value is the standard value of n color blocks in the standard color card; x is a color correction matrix coefficient, ">
S3: correcting the to-be-corrected numerical values R, G, B of n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrixRGB to color modelThe conversion formula of each component is used for obtaining the value L of each component of the converted color model 1 、M 1 、N 1 ；
S5: standard value L of each component according to color model in standard color card b 、M b 、N b And component values L of the converted color model 1 、M 1 、N 1 Establishing an objective function, and enabling the objective function f to be equal to the sum of root mean square of differences of the standard component values in the n color cards and the component values of the corresponding converted color model:
s6: fitting the objective function according to the constraint function and the objective function under the condition that the value of the objective function is minimum, obtaining a color correction matrix coefficient X, and correcting the image color according to the color correction matrix coefficient X.
Further, in the step of S5, the method further comprises increasing the weight of each component in the color model on the root mean square of the difference value of each standard component value and the component of the corresponding converted color model:
wherein k is 1 、k 2 K 3 For the root mean square weight coefficient of each difference value, k 1 、k 2 K 3 Is a real number.
Further, the method includes setting weights in the objective function that highlight desired components of desired color patches in the standard color chart:
wherein i represents the serial number of the color block required in the selected standard color card; o represents the need for highlighting in the color modelWhich may be one or more of L, M and N; k (k) 4 The weight, k, representing the ith color block 4 Is a real number.
Further, the method further comprises the step of performing a color correction test according to the obtained color correction matrix coefficient X after the color correction matrix coefficient X is obtained, and adjusting the weight of the root mean square of the difference value of each component according to the test result.
Further, the color model is an HSI color model, an HSL color model, a YUV color model, or a Lab color model.
Further, in step S4, the obtained corrected matrix is converted into each component value L of the color model by a geometric derivation method, a coordinate transformation method, a segmentation definition method, a Bajon approximation method, or a standard model method 1 、M 1 、N 1 。
Further, fitting the objective function by a least square method or linear regression to obtain the color correction matrix coefficient X according to the constraint function and the objective function under the condition that the value of the objective function is minimum.
Further, the sum of each column of the color correction matrix coefficients X tends to be 1.
The present invention also provides a computer storage medium comprising a computer program which, when executed, implements the image color correction method provided by the present invention. .
The invention also provides an endoscope, which is used for carrying out color correction on the image by adopting the image color correction method provided by the invention.
In summary, the present invention photographs the standard color card through the coefficient to be corrected to obtain R, G, B to be corrected in the standard color card and each component of the color model, and simultaneously establishes a constraint function according to the standard value of the RGB component in the standard color card and the value to be measured of RGB, establishes an objective function according to the sum of the standard component of the same component in each color card and the root mean square of the difference value of the converted components, and fits the objective function and the constraint function to obtain a color correction matrix coefficient, and the sum of each column of the color correction matrix coefficient X tends to be 1. The method is simple and convenient, avoids a complex image data analysis process, and can replace objective functions and constraints in real time according to actual requirements to obtain color correction coefficients meeting requirements.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention, as well as the preferred embodiments thereof, together with the following detailed description of the invention, given by way of illustration only, together with the accompanying drawings.
Drawings
Fig. 1 is a schematic control flow chart of an image color correction method provided by the invention.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description of the present invention is given with reference to the accompanying drawings and preferred embodiments.
The invention aims to provide an image color correction method, a storage medium and an endoscope. The image color correction method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual requirements.
The color model mentioned in the present invention refers to other color spaces suitable for computer calculation adjustment, such as HSI (Hue, saturation, brightness) color model, HSL (Hue, saturation, brightness) color model, YUV (luminence, chrominance, chroma; brightness, chroma, concentration) color model, lab color model, and the like, in addition to RGB (Red, green, blue) color model.
Fig. 1 is a schematic control flow chart of an image color correction method provided by the present invention, and as shown in fig. 1, the automatic exposure control method provided by the present invention includes the following steps:
s1: the standard color chart is photographed by the system to be corrected to obtain the values to be corrected of R, G, B of n color patches in the color chart, and the values to be corrected of each component L, M, N of the color model (L, M, N refers to each component in the color model, and is not limited to three, and may also contain other components according to the definition of the color model). Wherein n may represent all color blocks in the standard color card, or may be a part selected according to needs, such as 12 color blocks. The system to be corrected comprises an image pickup device and can be used for shooting the color card.
S2: establishing an inequality constraint function: and A is X-B is less than or equal to K.
Wherein A is the value R, G, B to be corrected of n color blocks in the standard color card; b is the standard value R of n color blocks in the standard color card b 、G b 、B b The method comprises the steps of carrying out a first treatment on the surface of the X is a color correction matrix coefficient; the constraint K of the inequality depends on the actual model requirements, and differences in the K values will result in differences in the color correction matrix coefficients X. Namely:
the number of rows n in the matrix is determined by the number of color patches selected in the standard color card. In order to ensure that the color correction matrix coefficient X does not affect the white balance of the image after correcting the image, the sum of each column of the color correction matrix coefficient X tends to be 1; i.e. to ensure that the white image is still white after correction via the color correction matrix coefficient X.
S3: correcting the to-be-corrected numerical values R, G, B of n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrixAnd converting the RGB into a conversion formula of each component of the color model to obtain a value L of each component of the converted color model 1 、M 1 、N 1 . The conversion algorithm of each component of the RGB to color model can be, but not limited to, a geometric derivation method, a coordinate transformation algorithm, a segmentation definition method, a Bajon approximation algorithm, a standard model algorithm, or the like.
S5: standard value L of each component according to color model in standard color card b 、M b 、N b And component values L of the color model after conversion in the color model 1 、M 1 、N 1 And establishing an objective function, wherein the objective function f is equal to the sum of the root mean square of the difference value of each standard component value in the n color cards and the corresponding component value of the converted color model.
Further, in order to better meet the practical needs, the weight coefficient of each component in each color model may be added before each root mean square of the difference value, so as to emphasize a certain component, that is, at this time, the objective function f is:
wherein k is 1 、k 2 K 3 For the root mean square weight coefficient of each difference value, k 1 、k 2 K 3 Is a real number.
Further, the objective function may be set to emphasize a certain desired component in a certain desired color block in the standard color chart, such as the color of the ith color block, where the objective function f may be:
wherein i represents the selected standard colorThe number of the color block required in the card, O, represents the component to be highlighted in the color model, which may be one or more of L, M and N; k (k) 4 The weight, k, representing the ith color block 4 Is a real number.
S6: and fitting the objective function according to the constraint function and the objective function under the condition that the value of the objective function is minimum, and obtaining a color correction matrix coefficient X. The fitting method may be, but is not limited to, least squares, nonlinear regression, unconstrained nonlinear fitting functions, or nonlinear fitting with constraints, etc.
S7: and performing a color correction test according to the obtained color correction matrix coefficient X, and adjusting the weight of the difference root mean square of each component according to the test result. After the image is corrected by using the color correction matrix coefficient X, if the corrected image is not satisfied, the weight of the root mean square of the difference value of each component in the objective function f may be fine-tuned, for example, a component of a certain color block is added, and the precondition of the fine-tuning is to ensure that the result of the objective function f does not change much.
In this embodiment, shooting is performed on a standard color card through coefficients to be corrected to obtain R, G, B to be corrected in the standard color card and components of a color model, meanwhile, a constraint function is established according to standard values of RGB components in the standard color card and values to be detected of RGB, an objective function is established according to sum of root mean square of differences of standard components of the same components in the standard color card and converted components, fitting is performed through the objective function and the constraint function to obtain color correction matrix coefficients, colors are corrected through the color correction matrix coefficients, an RGB color model which is not suitable for computer processing can be changed into other color models which are more suitable for calculation processing, and compared with an existing correction method based on image color distribution characteristics, color space mapping and spectral reflectivity restoration, the method is simple and convenient, avoids complex image data analysis processes, and meanwhile, the objective function and constraint can be replaced in real time according to actual requirements, and the color correction coefficients meeting requirements are obtained.
The color correction method provided by the present invention is explained in more detail below in the HSI (Hue, saturation, brightness) color model.
S1: the standard color chart is photographed by the system to be corrected to obtain values to be corrected of R, G, B of n color patches in the color chart and values to be corrected of each component H, S, I of the color model, where n may be 12 in this embodiment, that is, 12 color patches of the standard color chart are taken.
S2: establishing an inequality constraint function: X-B is less than or equal to K, wherein A is a value R, G, B to be corrected of n color blocks in a standard color card; b is the standard value R of n color blocks in the standard color card b 、G b 、B b The method comprises the steps of carrying out a first treatment on the surface of the X is a color correction matrix coefficient; the constraint K of the inequality depends on the actual model requirements, and differences in the K values will result in differences in the color correction matrix coefficients X.
For example, if the value to be corrected of the 2 nd color patch in the standard color card is: r is 139, G is 11, B is 6; then a= [139 11 6], it will be appreciated that since in this embodiment the standard color card selects 12 color patches, a should be a 12 x 3 matrix; similarly, if the standard value of the 2 nd color block in the standard color chart is R value 179, g value 42, and B value 50, then b= [179 42 50], and for the same reason, also B is a 12×3 matrix.
S3: correcting the to-be-corrected numerical values R, G, B of 12 color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: after the corrected matrix is obtained, the values of H, S and I are obtained according to the RGB to HSI conversion formula, which may be, but not limited to, geometric derivation, coordinate transformation, segmentation definition, bajon approximation, or standard model. Taking geometric derivation as an example:
s5: defining H values after conversion to HSI color space as a 1×12 matrix H 1 S value is 1×12 matrix S 1 And L has a value of 1×12 matrix L 1 . To obtain an objective function:
at this time, the weight of a certain component may be specified. If the luminance component does not need to make a request when the tone request is high, the weight of the H component may be high, the weight of the H component is 0.7, the weight of the s component is 0.3, and the weight of the L component is 0, that is, the objective function that can be obtained at this time is:
it will be appreciated that if the saturation requirement is high, the weight of the S component may be increased.
If the requirements on a certain color, such as red, are also required to be increased while the requirements on the brightness are higher, the weight of the red color block can be increased, if the red color block is the 3 rd color block in the selected standard color blocks, the weight given by the color block is 0.4, the weight of H is 0.5, and the weight of S is 0.1, at this time, the objective function can be obtained:
s6: after the inequality constraint function and the objective function are established, fitting the objective function according to the constraint function and the objective function under the condition that the value of the objective function is minimum, and obtaining a color correction matrix coefficient X.
It will be appreciated that in this step, the method of fitting may be selected as desired, such as least squares or non-linear regression.
After obtaining the color correction matrix coefficient X, performing correction test on the color according to the color correction matrix coefficient X, and weighting k of the root mean square of the difference value of each component according to the test result 1 、k 2 、k 3 K 4 Fine tuning is performed to obtain the most desirable results.
In summary, according to the method, the standard color card is shot through the coefficient to be corrected to obtain R, G, B to be corrected in the standard color card and each component of the color model, meanwhile, a constraint function is built according to the standard value of the RGB component in the standard color card and the RGB value to be detected, an objective function is built according to the sum of the standard component of the same component in each color card and the difference root mean square of the converted components, the objective function and the constraint function are used for fitting to obtain a color correction matrix coefficient X, the color correction matrix coefficient X is used for correcting the color, and an RGB color model which is not suitable for computer processing can be changed into other color models which are more suitable for calculation processing.
The present invention also provides a computer storage medium comprising a computer program which, when executed, implements the image color correction method provided by the present invention.
The invention also provides an endoscope which adopts the image color correction method provided by the invention to correct the image color.
The present invention is not limited to the above-mentioned embodiments, but is intended to be limited to the following embodiments, and any modifications, equivalent changes and variations in the above-mentioned embodiments can be made by those skilled in the art without departing from the scope of the present invention.
Claims (10)
1. An image color correction method, characterized in that: the method comprises the following steps:
s1: shooting a standard color card by using a system to be corrected to obtain values to be corrected of R, G, B of n color blocks in the color card and values to be corrected of components L, M, N of a color model;
s2: establishing an inequality constraint function: and A is X-B is less than or equal to K, wherein,r, G, B is the value to be corrected of n color blocks in the standard color card; />R b 、G b 、B b The standard value is the standard value of n color blocks in the standard color card; x is a color correction matrix coefficient, K values are determined according to model requirements, and the difference of the K values leads to the difference of the X values, ">
S3: correcting the to-be-corrected numerical values R, G, B of n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrixAnd converting the RGB into a conversion formula of each component of the color model to obtain a value L of each component of the converted color model 1 、M 1 、N 1 ；
S5: standard value L of each component according to color model in standard color card b 、M b 、N b And component values L of the converted color model 1 、M 1 、N 1 Establishing an objective function, and enabling the objective function f to be equal to the sum of root mean square of differences of the standard component values in the n color cards and the component values of the corresponding converted color model:
s6: and fitting the objective function according to the constraint function and the objective function under the condition that the value of the objective function is minimum, and obtaining a color correction matrix coefficient X.
2. The image color correction method according to claim 1, characterized in that: in step S5, the method further comprises increasing the weight of each component within the color model on the root mean square of the difference value of each standard component value and the corresponding component of the converted color model:
wherein k is 1 、k 2 K 3 For the root mean square weight coefficient of each difference value, k 1 、k 2 K 3 Is a real number.
3. The image color correction method according to claim 2, characterized in that: the method further includes setting weights in the objective function that highlight desired components of desired color patches in the standard color chart:
wherein i represents the serial number of the color block required in the selected standard color card; o represents the component of the color model that needs to be highlighted, which is one or more of L, M and N; k (k) 4 The weight, k, representing the ith color block 4 Is a real number.
4. The image color correction method according to claim 1, characterized in that: the method further comprises the step of carrying out a color correction test according to the obtained color correction matrix coefficient X after the color correction matrix coefficient X is obtained, and adjusting the weight of the difference root mean square of each component according to the test result.
5. The image color correction method according to claim 1, characterized in that: the color model is an HSI color model, an HSL color model, a YUV color model or a Lab color model.
6. The image color correction method according to claim 1, characterized in that: in step S4, the obtained corrected matrix is converted into component values L of the color model by a geometric derivation method, a coordinate transformation method, a segmentation definition method, a Bajon approximation algorithm, or a standard model method 1 、M 1 、N 1 。
7. The image color correction method according to claim 1, characterized in that: fitting the objective function by a least square method or linear regression to obtain the color correction matrix coefficient X according to the constraint function and the objective function under the condition that the value of the objective function is minimum.
8. The image color correction method according to claim 1, characterized in that: the sum of each column of the color correction matrix coefficients X tends to be 1.
9. A computer storage medium, characterized by: the computer storage medium comprising a computer program which, when executed, implements the image color correction method of any one of claims 1 to 8.
10. An endoscope, characterized in that: an image color correction method according to any one of claims 1 to 8.
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| CN111861922B (en) * | 2020-07-21 | 2024-09-17 | 浙江大华技术股份有限公司 | Color correction matrix adjusting method and device and storage medium |
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| CN115456894A (en) * | 2022-09-02 | 2022-12-09 | 北京墨境天合数字图像科技有限公司 | Video production color correction method, device, equipment and storage medium |
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