CN117178286A - Bokeh processing method, electronic device and computer-readable storage medium - Google Patents

Abstract

A bokeh processing method is disclosed. The method includes: obtaining DSLR camera parameters including focal length and F value; obtaining an image, a focus distance and a depth map corresponding to the image; obtaining the bokeh size of each pixel of the image based on the DSLR camera parameters, focus distance and depth map, to generate a bokeh size map; and perform bokeh processing on the image based on the bokeh size map.

Description

Bokeh processing method, electronic device and computer-readable storage medium

Technical field

The present disclosure relates to a method for bokeh processing, and in particular, to a method for accurately reproducing high-quality bokeh equivalent to the bokeh created by a digital single lens reflex (DSLR) camera, An electronic device for executing the method and a computer-readable storage medium storing a program for implementing the method.

Background technique

In recent years, techniques for artificially generating images with bokeh have been widely used. In an image with bokeh, subjects such as people should be shown clearly, while backgrounds such as buildings or the sky, on the other hand, should be blurred. For example, in the area occupied by the subject, the bokeh size/strength is set to 0, and the bokeh size in other areas increases with distance from the subject.

The size/area of the image sensor of an electronic device such as a smartphone is smaller than that of a DSLR camera with a large sensor such as a 35mm sensor. Due to the small sensor size, it is inevitable that the size of the bokeh generated based on images taken with electronic devices is smaller than that of images taken with a DSLR camera. Therefore, images with bokeh generated by electronic devices may look unnatural. To improve the quality of images with bokeh, it is known to use the depth value of a depth map to determine the size of the bokeh. However, even using this method, it is difficult to obtain images with the same bokeh as those taken with a DSLR camera.

Contents of the invention

The present disclosure aims to solve at least one of the above technical problems. Therefore, the present disclosure needs to provide a method for bokeh processing and an electronic device implementing the method.

According to the present disclosure, a method for bokeh processing includes: acquiring DSLR camera parameters including focal length (f) and focal ratio F value (A), acquiring an image, a focus distance (D), and a depth map corresponding to the image , obtain the bokeh size of each pixel of the image based on the DSLR camera parameters, focus distance and depth map to generate a bokeh size map, and perform bokeh processing on the image based on the bokeh size map.

According to the present disclosure, an electronic device includes a processor and a memory for storing instructions. When executed by a processor, the instructions cause the processor to perform methods in accordance with the present disclosure.

According to the present disclosure, a computer-readable storage medium is provided with a computer program stored thereon. The computer program is executed by a computer to implement the method according to the present disclosure.

Description of drawings

These and/or other aspects and advantages of embodiments of the present disclosure will become apparent and better understood from the following description taken with reference to the following drawings.

1A is a functional block diagram showing the configuration of an electronic device according to an embodiment of the present disclosure.

1B is a functional block diagram of an image signal processor in an electronic device according to an embodiment of the present disclosure.

Figure 2 is a flowchart for generating an image with bokeh, according to an embodiment of the present disclosure.

Figure 3 is an example of a user interface for entering DSLR camera parameters.

Figure 4A shows an example of an image captured by a camera module.

FIG. 4B shows an example of a depth map corresponding to the image shown in FIG. 4A.

Figure 5 shows an example of a bokeh size map generated by using a method according to an embodiment of the present disclosure.

Figure 6 shows an example of an image with bokeh generated by using a method according to an embodiment of the present disclosure.

FIG. 7 is a diagram illustrating the focus of bokeh based on DSLR camera parameters.

FIG. 8 is a diagram illustrating changes in bokeh size within a depth of field (DoF) range.

Detailed ways

Embodiments of the present disclosure will be described in detail, and examples of the embodiments are illustrated in the accompanying drawings. Throughout the description, identical or similar elements and elements having the same or similar function are designated by the same reference numerals. The embodiments described herein with reference to the drawings are illustrative and intended to illustrate the disclosure but should not be construed to limit the disclosure.

<Electronic Equipment 100>

Electronic device 100 will be described with reference to FIG. 1A. 1A is a functional block diagram showing an example of the configuration of the electronic device 100 according to an embodiment of the present disclosure.

The electronic device 100 is a mobile device such as a smartphone, a tablet terminal, or a mobile phone, but may be other types of electronic devices equipped with one or more camera modules.

As shown in Figure 1A. The electronic device 100 includes a stereo camera module 10 , a distance sensor module 20 and an image signal processor 30 , a global navigation satellite system (GNSS) module 40 , a wireless communication module 41 , a codec 42 , a speaker 43 , and a microphone 44 , display module 45, input module 46, inertial measurement unit (inertial measurement unit, IMU) 47, main processor 48 and memory 49.

The stereo camera module 10 includes a master camera module 11 and a slave camera module 12 for binocular stereo viewing, as shown in Figure 1A. Camera module 10 can capture video at a given frame rate.

The main camera module 11 includes a first lens 11a capable of focusing on a subject, a first image sensor 11b that detects an image input via the first lens 11a, and a first image sensor driver 11c that drives the first image sensor 11b, as shown in FIG. Shown in 1A.

The slave camera module 12 includes a second lens 12a capable of focusing on a subject, a second image sensor 12b that detects an image input via the second lens 12a, and a second image sensor driver 12c that drives the second image sensor 12b, as shown in FIG. Shown in 1A.

The main camera module 11 captures main camera images. Slave camera images are captured from the camera module 12 . The master camera image and the slave camera image may be color images such as RGB images or monochrome images.

Through stereo matching technology, a depth map can be generated based on the main camera image and the slave camera image. Specifically, the amount of parallax is calculated for each corresponding pixel of the stereoscopic image (ie, the main camera image and the slave camera image). The depth value increases as the amount of parallax increases. The depth map includes the depth value of each pixel in the image.

Distance sensor module 20 captures a depth map. For example, the distance sensor module 20 is a time-of-flight (ToF) camera, and a ToF depth map is captured by emitting pulsed light to a subject and detecting light reflected from the subject. The ToF depth map indicates the actual distance between the electronic device 100 and the subject. Optionally, the distance sensor module can be omitted.

An image signal processor (ISP) 30 controls the master camera module 11 , the slave camera module 12 and the distance sensor module 20 . The ISP 30 also performs image processing on images captured by the stereo camera module 10 . Specifically, the ISP 30 acquires original images from the camera module 10 . The original image is either the master camera image or the slave camera image. ISP 30 performs bokeh processing on the original image to generate an image with bokeh. An image with bokeh can be generated based on the original image and the bokeh size map, which will be described later.

When the camera module 10 captures an image, the ISP 30 acquires the autofocus area in the captured image from the stereo camera module 10 . The autofocus area represents the in-focus area. For example, the autofocus area appears as an autofocus rectangle. The autofocus area is obtained through the autofocus operation of the camera module 10 .

ISP 30 gets the focus distance or subject distance. The focus distance is the distance between the subject and the camera module 10 . More precisely, the focus distance indicates the distance between the focus plane and the principal point of the lens 11a (11b).

ISP 30 can calculate focus distance based on depth map and autofocus area. For example, the focus distance is obtained by calculating a representative value of the depth value in the autofocus area. The representative value can be the mean, median, or interquartile range value (e.g., third quartile, first quartile).

The GNSS module 40 measures the current location of the electronic device 100 . The wireless communication module 41 performs wireless communication with the Internet. The codec 42 bidirectionally performs encoding and decoding using a predetermined encoding/decoding method. The speaker 43 outputs sound based on the sound data decoded by the codec 42 . The microphone 44 outputs sound data to the codec 42 based on the input sound.

The display module 45 displays various information, such as images captured in real time by the camera module 10 , a user interface (UI), and images with bokeh generated by the ISP 30 .

The input module 46 inputs information through user operations. The input module 46 is a touch panel, a keyboard, or the like. Input module 46 inputs instructions to capture and store images displayed on display module 45 . Additionally, input module 46 inputs user-selected DSLR camera parameters (described below).

The IMU 47 detects the angular velocity and acceleration of the electronic device 100 . The posture of the electronic device 100 can be grasped from the measurement results of the IMU 47 .

The main processor 48 controls the Global Navigation Satellite System (GNSS) module 40, the wireless communication module 41, the codec 42, the speaker 43, the microphone 44, the display module 45, the input module 46 and the IMU 47.

Memory 49 stores data for images, data for depth maps, various camera parameters to be used in image processing, and programs running on image signal processor 30 and/or main processor 48 .

Next, the ISP 30 is described in detail with reference to FIG. 1B.

The ISP 30 includes a first acquisition unit 31 , a second acquisition unit 32 , an acquisition unit 33 and an execution unit 34 .

The first acquisition unit 31 is configured to acquire DSLR camera parameters including focal length and F value. DSLR camera parameters are the camera parameters of a digital SLR camera. Camera parameters include the type of image sensor and the type of lens. The DSLR camera parameters are different from the camera parameters of the camera module 10 installed on the electronic device 100 .

DSLR camera parameters include at least focal length and F-number. DSLR camera parameters may also include the size and/or resolution of the DSLR image sensor. A DSLR image sensor is the image sensor of a DSLR camera.

The second acquisition unit 32 is used to acquire images, focus distances and depth maps. The depth map corresponds to the acquired image.

The obtaining unit 33 is configured to obtain the bokeh size of each pixel of the image based on the DSLR camera parameters, the focus distance, and the depth map to generate a bokeh size map.

The execution unit 34 is configured to perform bokeh processing on the image based on the bokeh size map.

<Bokeh processing method>

A bokeh processing method according to an embodiment of the present disclosure will be described with reference to the flowchart shown in FIG. 2 .

In step S1, the display module 45 displays a user interface (UI) that allows the user to input DSLR camera parameters.

FIG. 3 shows an example of a UI displayed by the display module 45. Users can enter DSLR camera parameters through the UI. In this example, the user can select the type of DSLR image sensor, which is "645", "35mm" or "APS-C". Users can also select the lens type, namely focal length (20mm to 100mm) and F-number (F1.4 to F11). After selecting the DSLR camera parameters, the user clicks the "Save" button to save the selected parameters in memory 49.

Alternatively, a UI allowing the user to select the resolution of the DSLR image sensor from candidates may be displayed.

In step S2, the first acquisition unit 31 of the ISP 30 acquires the DSLR camera parameters input by the user in step S1. Specifically, the first acquisition unit 31 reads the input DSLR camera parameters from the memory 49 .

In step S3, the second acquisition unit 32 of the ISP 30 acquires the image (ie, the original image), the focus distance, and the depth map corresponding to the original image. Specifically, when a user takes photos/videos using the electronic device 100, the stereo camera module 10 captures a main camera image and a slave camera image. The second acquisition unit 32 acquires the main camera image or the slave camera image as the original image.

With the help of stereo matching technology, ISP 30 generates a depth map based on the main camera image and the slave camera image.

Alternatively, a depth map may be obtained from the distance sensor module 20.

The second acquisition unit 32 acquires the autofocus area from the camera module 10 and acquires the focus distance by calculating a representative value of the depth value in the autofocus area.

Alternatively, the second acquisition unit 32 may directly acquire the focus distance from the camera module 10 . In this case, the focus distance is determined by the autofocus operation of the camera module 10 .

Figure 4A shows an example of an image captured by camera module 10. The image includes three objects S1, S2 and S3, which are placed on the table in the order of object S1, object S2 and object S3 from the front. In the example shown in Figure 4A. The autofocus area R is on the subject S2.

FIG. 4B shows an example of a depth map corresponding to the acquired image shown in FIG. 4A. Depth maps are grayscale images. For example, the brightness of areas in the depth map decreases as the distance from the electronic device 100 increases.

Next, in step S4, for each pixel of the acquired image, the obtaining unit 33 of the ISP 30 calculates the bokeh size based on the DSLR camera parameters, the focus distance, and the depth map. Therefore, a bokeh size map is generated.

Bokeh size can be calculated by the following equation:

Among them, C is the bokeh size, f is the focal length, A is the F value, D is the focus distance, and d is the depth value of the corresponding pixel in the depth map.

FIG. 5 shows an example of the bokeh size map generated in step S4. Bokeh size images are grayscale images. Bokeh Size The brightness of an area in the image increases as the bokeh size of that area increases. In the example shown in Figure 5, the area indicating the focus object S2 has the lowest brightness (ie the smallest bokeh size). On the other hand, the area indicating the focus object S1 has the highest brightness (ie, the largest bokeh size).

In step S5, the execution unit 34 of the ISP 30 performs bokeh processing on the original image based on the bokeh size map generated in step S4. Therefore, images with bokeh can be obtained.

Bokeh processing can be performed by applying a smoothing filter to the original image. The smoothing filter is a filter generated based on the bokeh size map. For example, a smoothing filter is a Gaussian filter with a standard deviation calculated based on the bokeh size in the bokeh size map. Bokeh size can be converted to standard deviation via the following equation.

where σ is the standard deviation, C is the bokeh size, and pp is the pixel pitch of the DSLR image sensor.

Pixel pitch pp can be calculated by the following equation:

Where, S is the area of the DSLR image sensor, and N _p is the number of pixels in the DSLR image sensor. S and N _p are both DSLR camera parameters.

Specifically, execution unit 34 generates a Gaussian kernel for each pixel in the image. Determine the coefficients of the Gaussian kernel based on the standard deviation σ. Then, for each pixel in the image, execution unit 34 convolves a Gaussian kernel on the corresponding pixel.

For example, the sizes of Gaussian kernel are 3×3, 8×8, 16×16, but it is not limited to any specific size. The kernel size can be determined based on the standard deviation σ. For example, kernel size increases as standard deviation decreases. The core size can also be determined based on the computing power of the ISP 30. For example, core size increases with increasing computing power.

Figure 6 shows an example of the image with bokeh generated in step S5. Focused object S2 is shown clearly, while objects S1 and S3 are greatly blurred.

FIG. 7 shows a situation where the user P of the electronic device 100 takes a photo or video of the subject person S and there are flowers FG in the foreground and trees BG in the background. As shown in FIG. 7 , over the entire distance, the bokeh size generated based on the DSLR camera parameters according to the above method (solid line) is larger than the bokeh size generated based on the actual camera parameters of the electronic device 100 (dashed line). Therefore, large bokeh of flowers FG and trees BG can be obtained.

Furthermore, it can be seen from Figure 7. The curve of the bokeh size near the subject person S is asymmetrical in the distance direction. That is to say, the bokeh size in front of the subject person S is larger than the bokeh size behind the subject person S. This can be understood from the above equation for calculating bokeh size.

It’s important to note that there are many ways to deal with bokeh. The bokeh processing in step S5 is not limited to the above method, as long as the bokeh size map is used.

The DSLR camera parameters can be obtained from preset parameters stored in the memory 49 in advance. In this case, the above-mentioned UI does not need to be displayed, that is, step S1 is not necessary.

Optionally, at least one of the above steps may be performed by the main processor 48 .

Optionally, you can change the size of the bokeh near the subject. Specifically, the bokeh size in the depth of field (DoF) may be changed to a value smaller than the calculated bokeh size. Normally, all bokeh sizes in DoF are changed to 0. In this case, the obtaining unit 33 calculates the bokeh size through the above-mentioned equation, and changes the bokeh size in the DoF to a predetermined value (for example, 0) smaller than the calculated bokeh size.

Figure 8 shows the same situation as Figure 7 described above. As shown in Figure 8, the bokeh size in DoF is set to 0. In other words, the bokeh size is set to 0 within the first range of the distance Tf in front of the subject S and in the second range of the distance Tr behind the subject S. The bokeh size in the first range and the second range is set to 0, so that the subject person S can be displayed more clearly.

DoF can be calculated based on focal length (f), F-number (A), focus distance (D), and allowed circle of confusion (δ). Specifically, DoF is calculated by the following equation.

DoF＝T _f +T _r

Among them, T _f is the foreground depth, T _r is the back depth of field, δ is the allowable circle of confusion, f is the focal length, A is the F value, and D is the focus distance.

The allowed circle of confusion δ is calculated by the following equation.

δ＝Max{pp,adr}

adr=1.22×λ×A,

where δ is the allowed circle of confusion, Max is a function that returns the larger of the two independent variables, pp is the pixel pitch of the DSLR image sensor, adr is the Airy disk radius, and λ is the representative wavelength (for example, 530nm), and a is the F value.

As described above, according to embodiments of the present disclosure, by performing bokeh processing using a bokeh size map generated based on DSLR camera parameters, high-quality bokeh equivalent to bokeh created by a DSLR camera can be accurately reproduced. In other words, it is possible to generate images with natural and large bokeh.

For example, even if the picture or video was taken using a smartphone or the like, a smartphone with a relatively small image sensor can generate an image with large bokeh (equivalent to the bokeh created by a DSLR camera with a large image sensor).

In the description of the embodiments of the present disclosure, it should be understood that terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front" , "rear", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise" and " The term "counterclockwise" should be interpreted to refer to a direction or position as described or illustrated in the figures in question. These relative terms are used only to simplify the description of the present disclosure and do not indicate or imply that the device or element mentioned must have a particular orientation, or must be constructed or operated in a particular orientation. Therefore, these terms should not be construed as limiting the present disclosure.

Furthermore, terms such as “first” and “second” are used herein for descriptive purposes and are not intended to indicate or imply relative importance or significance, or to imply the number of technical features indicated. Thus, features defined as "first" and "second" may include one or more of these features. In the description of the present disclosure, "plurality" means "two or more than two" unless otherwise stated.

In the description of the embodiments of the present disclosure, unless otherwise specified or limited, the terms "mounted", "connected", "coupled", etc. are used broadly, and may be, for example, a fixed connection, a detachable connection, or an integral Connection; it can also be a mechanical or electrical connection; it can also be a direct connection or an indirect connection through an intermediate structure; it can also be an internal communication between two elements that a person skilled in the art can understand according to the specific situation.

In embodiments of the present disclosure, unless otherwise specified or limited, structures wherein a first feature is "on" or "under" a second feature may include the first feature in direct contact with the second feature embodiments, and may also include embodiments in which the first feature and the second feature are not in direct contact with each other, but are in contact through additional features formed therebetween. Additionally, a first feature "on", "over" a second feature, or "on top of" a second feature may include the first feature being "on" the second feature orthogonally or obliquely. Embodiments of two features being "on", "above" or "on top of" the second feature, or simply meaning that the first feature is at a higher height than the height of the second feature; And a first feature "below", "below" or "at" the bottom of a second feature may include the first feature being "below" the second feature, either orthogonally or obliquely. Embodiments of two features "below", "below" or "at" the bottom of a second feature may simply mean that the first feature is at a lower height than the height of the second feature.

Various embodiments and examples are provided in the above description to implement different structures of the present disclosure. To simplify the present disclosure, certain elements and arrangements are described above. However, these elements and arrangements are merely examples and are not intended to limit the disclosure. Furthermore, reference numbers and/or reference letters may be repeated in different examples of the present disclosure. This repetition is for simplicity and clarity and does not imply a relationship between the various embodiments and/or arrangements. Additionally, this disclosure provides examples of different processes and materials. However, those skilled in the art will understand that other processes and/or materials may also be used.

Throughout this specification, reference to "embodiments," "some embodiments," "exemplary embodiments," "examples," "particular examples," or "some examples" means that the particular embodiment or example is described in connection with that embodiment or example. Features, structures, materials, or characteristics are included in at least one embodiment or example of the present disclosure. Thus, the appearances of the above phrases throughout the specification are not necessarily referring to the same embodiment or example of the present disclosure. Furthermore, the specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

Any process or method depicted in a flowchart or otherwise described herein may be understood to include one or more modules, segments, or code of executable instructions for implementing specific logical functions or steps in the process. parts, and the scope of the preferred embodiments of the present disclosure includes other implementations in which those skilled in the art will understand that the functions may be performed in an order different from that shown or discussed, including in substantially the same order or the reverse order. .

The logic and/or steps otherwise described herein or illustrated in flowchart diagrams (e.g., a specific sequence of executable instructions for implementing the logical functions) may be embodied in any computer-readable medium. The readable medium will be used by or will be used by an instruction execution system, apparatus, or apparatus, such as a computer-based system, a system including a processor, or other system capable of obtaining instructions from an instruction execution system, apparatus, or apparatus that executes the instructions. Systems, equipment and devices are used in combination. For purposes of this specification, a "computer-readable medium" may be any device suitable for containing, storing, communicating, propagating, or transferring a program for use by or in combination with an instruction execution system, apparatus, or device . More specific examples of computer-readable media include, but are not limited to: an electrical connection having one or more wires (electronic device), a portable computer case (magnetic device), random access memory (RAM), read-only memory (read only memory, ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optic equipment and portable compact disk read-only memory (compact disk read-only memory, CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, since, for example, when a program is required to be obtained electronically, the paper or other suitable medium can be optically scanned and then used Compiled, decrypted or processed by other suitable means, and the program may then be stored in computer memory.

It should be understood that each part of the present disclosure can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, also in another embodiment, the steps or methods may be implemented by one or a combination of the following techniques known in the art: discrete logic with logic gates for implementing the logical function of the data signal Circuits, application-specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

Those skilled in the art should understand that all or part of the steps in the above exemplary methods of the present disclosure can be implemented by using program commands to related hardware. These programs may be stored in a computer-readable storage medium, and when run on a computer, these programs include one or a combination of the steps in the method embodiments of the present disclosure.

In addition, each functional unit of the embodiment of the present disclosure may be integrated in a processing module, or these units may be separate physical existences, or two or more units may be integrated in a processing module. Integrated modules can be implemented in the form of hardware or in the form of software function modules. When the integrated module is implemented in the form of a software function module and sold or used as an independent product, the integrated module can be stored in a computer-readable storage medium.

The above storage medium may be a read-only memory, a magnetic disk, a compact disc (CD), etc. Storage media may be transitory or non-transitory.

Although embodiments of the disclosure have been shown and described, those skilled in the art will understand that these embodiments are illustrative and are not to be construed as limiting the disclosure, and without departing from the scope of the disclosure, Changes, modifications, substitutions, and variations may be made in the embodiments.

Claims (20)

1. A method for foreground processing, comprising:

acquiring digital single inverse DSLR camera parameters including focal length and F value;

acquiring an image, a focusing distance and a depth map corresponding to the image;

based on the DSLR camera parameters, the focusing distance and the depth map, obtaining a foreground size of each pixel of the image to generate a foreground size map; and

and executing the foreground processing on the image based on the foreground size map.

2. The method of claim 1, wherein the DSLR camera parameters are obtained through a user interface allowing a user to input the DSLR camera parameters.

3. The method of claim 1, wherein the DSLR camera parameters are obtained from preset parameters.

4. A method according to any one of claims 1 to 3, wherein the focus distance is a representative value of a depth value in an autofocus area.

5. The method of any one of claims 1 to 4, wherein the dispersion Jing Daxiao is calculated by equation (1):

wherein C is the foreground size, F is the focal length, a is the F value, D is the focus distance, and D is the depth value of the corresponding pixel in the depth map.

6. The method according to any one of claims 1 to 5, wherein a scene size in the depth of field DoF is changed to a predetermined value smaller than the calculated scene size.

7. The method of claim 6, wherein the predetermined value is 0.

8. The method according to claim 6 or 7, wherein the DoF is calculated based on the focal length, the F value, the focus distance, and an allowable circle of confusion.

9. The method of claim 8, wherein the DoF is calculated by equations (2), (3) and (4):

DoF＝T _f +T _r …(2)

wherein T is _f Is the front depth of field, T _r Is the back depth of field, δ is the allowed circle of confusion, F is the focal length, a is the F value, and D is the focus distance.

10. The method according to any one of claims 1 to 9, wherein the foreground processing is performed by applying a smoothing filter generated based on the foreground size map to the image.

11. The method of claim 10, wherein the smoothing filter is a gaussian filter having a standard deviation calculated based on the foreground size.

12. The method of claim 11, wherein the standard deviation is calculated by equation (5):

where σ is the standard deviation, C is the foreground size, and pp is the pixel pitch of the DSLR image sensor.

13. The method of claim 11 or 12, wherein the size of the gaussian filter is determined based on the standard deviation.

14. An electronic device for image processing, comprising:

a first acquisition unit configured to acquire digital single inverse DSLR camera parameters including a focal length and an F value;

a second acquisition unit configured to acquire an image, a focusing distance, and a depth map corresponding to the image;

an obtaining unit configured to obtain a foreground size of each pixel of the image based on the DSLR camera parameters, the focusing distance, and the depth map, to generate a foreground size map; and

and the execution unit is configured to execute the foreground processing on the image based on the foreground size map.

15. The electronic device of claim 14, wherein the first acquisition unit acquires the DSLR camera parameters through a user interface allowing a user to input the DSLR camera parameters.

16. The electronic device of claim 14, wherein the first obtaining unit obtains the DSLR camera parameters from preset parameters.

17. The electronic device according to any one of claims 14 to 16, wherein the obtaining unit calculates the foreground size and changes the foreground size in the depth of field DoF to a predetermined value smaller than the calculated foreground size.

18. The electronic device of any of claims 14-17, wherein the execution unit is to perform the foreground processing by applying a smoothing filter generated based on the foreground size map to the image.

19. An electronic device for image processing comprising a processor and a memory for storing instructions, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of claims 1 to 13.

20. A computer readable storage medium having stored thereon a computer program, wherein the computer program is executed by a computer to implement the method of any of claims 1 to 13.