WO2022001648A1

WO2022001648A1 - Image processing method and apparatus, and device and medium

Info

Publication number: WO2022001648A1
Application number: PCT/CN2021/100019
Authority: WO
Inventors: 王勇威
Original assignee: 维沃移动通信有限公司
Priority date: 2020-06-30
Filing date: 2021-06-15
Publication date: 2022-01-06
Also published as: CN111866378A

Abstract

Provided are an image processing method and apparatus, and a device and a medium, which belong to the technical field of image processing. The image processing method comprises: acquiring N images, wherein the N images are images photographed by an image collection component at different focusing distances; dividing each of the N images into M areas; acquiring a pixel contrast value of each area of each image; determining coordinate information of a target object in a target image according to a pixel contrast value, wherein the target image is an image among the N images; and acquiring the target object in the target image according to the coordinate information.

Description

Image processing method, apparatus, equipment and medium

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to Chinese Patent Application No. 202010611475.X filed in China on Jun. 30, 2020, the entire contents of which are incorporated herein by reference.

technical field

The present application belongs to the technical field of image processing, and in particular relates to an image processing method, apparatus, device and medium.

Background technique

Matting is one of the most common operations in image processing, which is to separate a certain part of an image from the image. In the related art, a lasso tool, a marquee tool, a magic wand tool, a pen tool, etc. are usually used to manually cut out the image.

However, in the process of realizing the present application, the inventor found that there are at least the following problems in the related art: the cutout is inaccurate.

SUMMARY OF THE INVENTION

The purpose of the embodiments of the present application is to provide an image processing method, apparatus, device, and medium, which can solve the problem of inaccurate matting.

In order to solve the above technical problems, this application is implemented as follows:

In a first aspect, an embodiment of the present application provides an image processing method, including:

acquiring N images, wherein the N images are images captured by the image acquisition component at different focusing distances;

Divide each of the N images into M regions;

Get the pixel contrast value of each area of each image;

According to the pixel contrast value, determine the coordinate information of the target object in the target image, wherein the target image is an image in N images;

Obtain the target object in the target image according to the coordinate information.

In a second aspect, an embodiment of the present application provides an image processing apparatus, including:

a first acquisition module, configured to acquire N images, wherein the N images are images captured by the image acquisition component at different focusing distances;

a division module for dividing each of the N images into M regions;

The second acquisition module is used to acquire the pixel contrast value of each area of each image;

a determining module, configured to determine the coordinate information of the target object in the target image according to the pixel contrast value, wherein the target image is an image in N images;

The third acquiring module is used for acquiring the target object in the target image according to the coordinate information.

In a third aspect, embodiments of the present application provide an electronic device, the electronic device includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor, the program or instruction being The processor implements the steps of the method according to the first aspect when executed.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a program or an instruction is stored on the computer-readable storage medium, and when the program or instruction is executed by a processor, the method according to the first aspect is implemented A step of.

In a fifth aspect, an embodiment of the present application provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction, and implement the first aspect the steps of the method.

In the embodiment of the present application, each of the N images is divided into M areas, and the coordinate information of the target object in the target image is determined according to the pixel contrast value of each area of each image, and according to the coordinate information, Obtaining the target object in the target image is to realize the matting of the target object. Compared with artificially using tools to cut out the image in the related art, the embodiment of the present application can automatically cut out the target object, which can improve the accuracy of the image cutout.

Description of drawings

1 is a schematic flowchart of an image processing method provided by an embodiment of the present application;

2 is a schematic diagram of a target shooting scene provided by an embodiment of the present application;

3 is a schematic diagram of N images provided by an embodiment of the present application;

4 is a schematic diagram of area division provided by an embodiment of the present application;

5 is a schematic diagram of the results of the area classification provided by the embodiment of the present application;

6 is a schematic diagram of sub-regional display of objects provided by an embodiment of the present application;

7 is a schematic diagram of a processed target image provided by an embodiment of the present application;

8 is a schematic structural diagram of an image processing apparatus provided by an embodiment of the present application;

FIG. 9 is a schematic diagram of a hardware structure of an electronic device implementing an embodiment of the present application.

detailed description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

The terms "first", "second" and the like in the description and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It is to be understood that data so used may be interchanged under appropriate circumstances so that embodiments of the application can be practiced in sequences other than those illustrated or described herein. In addition, "and/or" in the description and claims indicates at least one of the connected objects, and the character "/" generally indicates that the associated objects are in an "or" relationship.

The image processing method, apparatus, device, and medium provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings through specific embodiments and application scenarios thereof.

FIG. 1 is a schematic flowchart of an image processing method provided by an embodiment of the present application. As shown in Figure 1, the image processing method may include:

S101: Acquire N images, where the N images are images captured by the image acquisition component at different focusing distances;

S102: Divide each of the N images into M regions;

S103: Obtain the pixel contrast value of each area of each image;

S104: determine the coordinate information of the target object in the target image according to the pixel contrast value, wherein the target image is the image in the N images;

S105: Acquire the target object in the target image according to the coordinate information.

It should be noted that, in the image processing method provided by the embodiments of the present application, the execution subject may be an image processing apparatus, or a control module in the image processing apparatus for executing the image processing method. In the embodiments of the present application, an image processing method performed by an image processing apparatus is used as an example to describe the image processing method provided by the embodiments of the present application.

The image processing device acquires N images; divides each image in the N images into M areas; acquires the pixel contrast value of each area of each image; determines the coordinates of the target object in the target image according to the pixel contrast value information; obtain the target object in the target image according to the coordinate information.

The specific implementation of the above steps will be described in detail below.

In some possible implementations of the embodiments of the present application, the image acquisition component may be a single image acquisition component.

Through the embodiment of the present application, a single image acquisition component is used to collect N images of the target shooting scene in the process of gradually changing the focus distance, and each image in the N images is divided into M areas; The pixel contrast value of each area determines the coordinate information of the target object in the target image, and obtains the target object in the target image according to the coordinate information. That is, the matting of the target object is realized, and the accuracy of the matting can be improved. In addition, it is not necessary to use multiple image acquisition components to collect multiple images for the target shooting scene, and use one image acquisition component to collect N images for the target shooting scene, so that the target object can be matted, and the cost is low.

In some possible implementations of the embodiments of the present application, the change trend of the focus distance may be a gradual change from small to large, or a gradual change from large to small.

Focusing distance refers to the distance between objects and images, which is the sum of the distance from the lens to the object and the distance from the lens to the photosensitive element.

In some possible implementations of the embodiments of the present application, the target shooting scene is shown in FIG. 2 . FIG. 2 is a schematic diagram of a target shooting scene provided by an embodiment of the present application. N images of the scene captured by the target shown in FIG. 2 in the process of gradually changing the focus distance are collected by using the image collection component, as shown in FIG. 3 . FIG. 3 is a schematic diagram of N images provided by an embodiment of the present application. Among them, Figure 3 shows four schematic diagrams of images.

In some possible implementations of the embodiments of the present application, taking one image among the four images shown in FIG. 3 as an example, the image is divided into M regions through S102 , as shown in FIG. 4 . FIG. 4 is a schematic diagram of area division provided by an embodiment of the present application. Among them, each square in Figure 4 represents an area.

In some possible implementations of the embodiments of the present application, each of the multiple regions obtained by dividing in S102 may include multiple pixels.

When each area may include multiple pixels, the pixel contrast value of the area may be the sum of the pixel contrast values of each pixel in the multiple pixels included in the area.

The pixel contrast value refers to the color difference between adjacent pixels.

In some possible implementations of the embodiments of the present application, each of the multiple regions obtained by dividing in S102 may include only one pixel.

When each area may include one pixel, the pixel contrast value of the area may be the pixel contrast value of one pixel included in the area.

According to the embodiment of the present application, each area includes only one pixel, that is, the image is divided according to the pixel granularity, so that the coordinates of the target object in the target object can be more accurate, and thus the accuracy of the map can be achieved.

In some possible implementations of the embodiments of the present application, S104 may include: classifying the M regions according to the change trend of the pixel contrast value and the change trend of the focus distance, and obtain a classification result; according to the classification result, determine that the target object is in the target image coordinate information in .

In some possible implementations of the embodiments of the present application, the change trend of the pixel contrast value includes but is not limited to: from large to small, from small to large, from large to small and then from small to large, and from small to large and then from large to small .

In some possible implementations of the embodiments of the present application, the changing trend of the focusing distance includes, but is not limited to: from large to small and from small to large.

In some possible implementations of the embodiments of the present application, classifying the M regions according to the change trend of the pixel contrast value and the change trend of the focus distance, and obtaining the classification result, may include: classifying the first region in the M regions into a classification result. The class is the background area, wherein the change trend of the pixel contrast value of the first area is the same as the change trend of the focus distance; the second area in the M areas is classified as the foreground area, wherein the pixel contrast value of the second area is the same. The change trend of , is opposite to that of the focus distance; the third area in the M areas is classified as the main area, wherein the change trend of the pixel contrast value of the third area and the change trend of the focus distance are the same first and then opposite. Or, the change trend of the pixel contrast value of the third area and the change trend of the focus distance are opposite first and then the same.

Wherein, the target object includes: at least one of a background area, a foreground area and a subject area.

Taking the area division shown in FIG. 4 as an example, the classified background area, foreground area and subject area are shown in FIG. 5 . FIG. 5 is a schematic diagram of a result of region classification provided by an embodiment of the present application.

In some possible implementations of the embodiments of the present application, the rate of change of the pixel contrast values of the background area, the foreground area, and the main body area may be different.

In some possible implementations of the embodiments of the present application, the M regions may also be classified according to the change rate of the pixel contrast value and the change trend of the focus distance to obtain a classification result.

Specifically, when the focusing distance increases from small to large, the areas in the M areas with the pixel contrast value change rate greater than the first rate are classified as foreground areas; the pixel contrast value change rate in the M areas is smaller than the second rate. The area is classified as a background area; the area in which the pixel contrast value change rate in the M areas is between the second rate and the first rate is classified as the main area, wherein the first rate is greater than the second rate.

When the focusing distance changes from large to small, the areas in the M areas with the change rate of the pixel contrast value greater than the third rate are classified as the background area; the areas in the M areas with the change rate of the pixel contrast value less than the fourth rate are classified as the background area. is the foreground area; the area where the pixel contrast value change rate in the M areas is between the fourth rate and the third rate is classified as the main area, wherein the third rate is greater than the fourth rate.

In some possible implementations of the embodiments of the present application, the target image may be an image focusing on the target object among the N images, that is, the target object may be an image focusing on the target object among the N images.

In the case where the target object is the main area, no matter whether the focusing distance changes gradually from small to large or from large to small, the pixel contrast value of the target object increases from small to large, and then from large to small. Therefore, the image corresponding to the maximum pixel contrast value of the target object can be determined as the target image. It can be understood that when the pixel contrast value of the target object is at the maximum value, the focus of the image acquisition component is just on the target object, that is, the image acquisition component takes the target object as the focus.

In some possible implementations of the embodiments of the present application, the image processing method provided by the embodiments of the present application may further include: performing first processing on the target object in the target image, and/or, performing the first processing on the target object in the target image except the target object. The other objects perform the second processing.

The embodiments of the present application do not limit the specific processing manners of the first processing and the second processing, and any available processing manners can be applied to the embodiments of the present application. For example, color burn processing, color gradient processing, soft light processing, sharpening processing, oil painting processing and color pencil processing and so on.

In some possible implementations of the embodiments of the present application, the first processing and the second processing may be set according to actual requirements.

In some possible implementations of the embodiments of the present application, when the target object is a person, the first processing may be a beauty processing.

In some possible implementations of the embodiments of the present application, the second processing may be blurring processing.

In the embodiment of the present application, when the target object is the main body region, the target object can be made clearer by performing blurring processing on other regions except the main body region in the target image.

In some possible implementations of the embodiments of the present application, the image processing method provided by the embodiments of the present application may further include: displaying the target object in the fourth area of the screen; displaying the target image in the fifth area of the screen except the target object other objects. That is, the target object in the target image is separated from other objects in the target image except the target object. Then, the second processing is performed on the target object displayed in the fourth area and the objects other than the target object in the target image displayed in the fifth area, respectively.

Exemplarily, the target object and other objects other than the target object in the target image are displayed in sub-regions, as shown in FIG. 6 . FIG. 6 is a schematic diagram of displaying objects in sub-regions provided by an embodiment of the present application.

Among them, in FIG. 6 , the target object is the main area, and other objects except the target object are the background area and the foreground area.

In the embodiment of the present application, by displaying the target object in the fourth area of the screen and displaying other objects in the target image except the target object in the fifth area of the screen, the target objects displayed in the fourth area of the screen can be respectively and performing the second processing on other objects other than the target object in the target image displayed in the fifth area of the screen, to avoid processing the target object and other objects other than the target object in the target image on the target image, Mishandling the target object or objects other than the target object in the target image.

In some possible implementations of the embodiments of the present application, the image processing method provided by the embodiments of the present invention may further include: combining the target object displayed in the fourth area that has undergone the first processing and the target object displayed in the fifth area that has undergone the second processing. Other objects in the target image except the target object are merged to obtain the processed target image.

Exemplarily, the target object and other objects other than the target object in the target image are displayed in sub-regions, as shown in FIG. 6 . After the target object and other objects except the target object in the target image are displayed in different areas, the first processing may be performed on the target object displayed in the fourth area, and/or the target object displayed in the fifth area except the target object may be subjected to the first processing. The second processing is performed on other objects other than the object. After the processing of the target object and other objects except the target object is completed, the two processed objects are merged to obtain the processed target image, as shown in Figure 7 . FIG. 7 is a schematic diagram of a processed target image provided by an embodiment of the present application.

In a possible implementation of the embodiment of the present application, the object in the target image, "the main area, the background area, and the foreground area" may also be displayed in three areas. Then, at least one object among the objects displayed in the sub-regions is processed, and after the object processing is completed, the three objects can be combined again to obtain a processed target image.

In this embodiment of the present application, by displaying objects in different regions, and then processing objects displayed in certain regions, the accuracy of image processing can be improved, and when objects are not displayed in regions, when an object is processed, other objects are processed. Mishandling of objects.

FIG. 8 is a schematic structural diagram of an image processing apparatus provided by an embodiment of the present application. As shown in FIG. 8 , the image processing apparatus 800 may include:

The first acquisition module 801 is configured to acquire N images, wherein the N images are images captured by the image acquisition component at different focusing distances;

A dividing module 802, configured to divide each of the N images into M regions;

The second acquisition module 803 is used to acquire the pixel contrast value of each area of each image;

Determining module 804 is used to determine the coordinate information of the target object in the target image according to the pixel contrast value, wherein the target image is the image in the N images;

The third obtaining module 805 is configured to obtain the target object in the target image according to the coordinate information.

In some possible implementations of the embodiments of the present application, the determining module 804 may include:

The classification sub-module is used to classify the M areas according to the change trend of the pixel contrast value and the change trend of the focus distance, and obtain the classification result;

The determining sub-module is used for determining the coordinate information of the target object in the target image according to the classification result.

In some possible implementations of the embodiments of the present application, the classification submodule may be specifically used for:

The first area in the M areas is classified as a background area, wherein the change trend of the pixel contrast value of the first area is the same as the change trend of the focus distance;

Classify the second area in the M areas as a foreground area, wherein the change trend of the pixel contrast value of the second area is opposite to the change trend of the focus distance;

The third area in the M areas is classified as the main area, wherein the change trend of the pixel contrast value of the third area and the change trend of the focus distance are the same first and then opposite, or the change of the pixel contrast value of the third area. The trend and the change trend of focus distance are opposite first and then the same;

In some possible implementations of the embodiments of the present application, the image processing apparatus 800 may further include:

The display module is used for displaying the target object in the fourth area of the screen, and displaying other objects in the target image except the target object in the fifth area of the screen.

In some possible implementations of the embodiments of the present application, the target image may be an image with the target object as the focus among the N images.

The image processing apparatus in this embodiment of the present application may be an apparatus, or may be a component, an integrated circuit, or a chip in a terminal. The apparatus may be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palmtop computer, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (personal digital assistant). assistant, PDA), etc., non-mobile electronic devices can be servers, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (television, TV), teller machine or self-service machine, etc., this application Examples are not specifically limited.

The image processing apparatus in this embodiment of the present application may be an apparatus having an operating system. The operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.

The image processing apparatus provided in the embodiments of the present application can implement each process in the image processing method embodiments shown in FIG. 1 to FIG. 7 , and in order to avoid repetition, details are not repeated here.

FIG. 9 is a schematic diagram of a hardware structure of an electronic device implementing an embodiment of the present application. As shown in FIG. 9 , the electronic device 900 includes but is not limited to: a radio frequency unit 901 , a network module 902 , an audio output unit 903 , an input unit 904 , a sensor 905 , a display unit 906 , a user input unit 907 , an interface unit 908 , and a memory 909 , and components such as the processor 910 .

The input unit 904 may include a graphics processor 9041 and a microphone 9042 . The display unit 906 may include a display panel 9061 . The user input unit 907 includes a touch panel 9071 and other input devices 9072 .

The memory 909 may be used to store software programs as well as various data. The memory 909 may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like.

Those skilled in the art can understand that the electronic device 900 may also include a power supply (such as a battery) for supplying power to various components, and the power supply may be logically connected to the processor 910 through a power management system, so that the power management system can manage charging, discharging, and power management. consumption management and other functions. The structure of the electronic device shown in FIG. 9 does not constitute a limitation to the electronic device. The electronic device may include more or less components than the one shown, or combine some components, or arrange different components, which will not be repeated here. .

The processor 910 is configured to: acquire N images, where the N images are images captured by the image acquisition component at different focusing distances; divide each of the N images into M regions; acquire each image The pixel contrast value of each area of then; according to the pixel contrast value, determine the coordinate information of the target object in the target image, wherein the target image is an image in N images; according to the coordinate information, obtain the target object in the target image.

In the embodiment of the present application, each of the N images is divided into M areas, and the coordinate information of the target object in the target image is determined according to the pixel contrast value of each area of each image, and according to the coordinate information, Obtaining the target object in the target image is to realize the matting of the target object. Compared with manually using tools to cut out images in the related art, the embodiments of the present application can automatically perform image matting on the target object, which can improve the accuracy of image matting.

In some possible implementations of the embodiments of the present application, the processor 910 may be specifically configured to:

According to the change trend of the pixel contrast value and the change trend of the focus distance, the M areas are classified, and the classification result is obtained;

According to the classification result, the coordinate information of the target object in the target image is determined.

In some possible implementations of the embodiments of the present application, the display unit 906 may be used for:

The target object is displayed in the fourth area of the screen, and other objects in the target image except the target object are displayed in the fifth area of the screen.

Optionally, an embodiment of the present application further provides an electronic device, including a processor 910, a memory 909, a program or instruction stored in the memory 909 and executable on the processor 910, the program or instruction being processed by the processor When 910 is executed, each process of the above image processing method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, details are not described here.

It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

Embodiments of the present invention further provide an electronic device configured to execute each process of the above image processing method embodiments, and can achieve the same technical effect, which is not repeated here to avoid repetition.

Embodiments of the present application further provide a computer-readable storage medium, where a program or an instruction is stored on the computer-readable storage medium, and when the program or instruction is executed by a processor, each process of the above image processing method embodiment is implemented, and can To achieve the same technical effect, in order to avoid repetition, details are not repeated here.

Wherein, the processor is the processor in the electronic device described in the foregoing embodiments. Examples of the computer-readable storage medium include non-transitory computer-readable storage media, such as computer read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc. .

An embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction to implement the above image processing method embodiments. Each process can achieve the same technical effect. In order to avoid repetition, it will not be repeated here.

An embodiment of the present invention further provides a computer program product, which can be executed by a processor to implement the various processes of the above image processing method embodiments, and can achieve the same technical effect. To avoid repetition, details are not repeated here. .

It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip, or the like.

It should be noted that, herein, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements, It also includes other elements not expressly listed or inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element. In addition, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in the reverse order depending on the functions involved. To perform functions, for example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to some examples may be combined in other examples.

From the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform, and of course hardware can also be used, but in many cases the former is better implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence or in a part that contributes to the prior art, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, CD-ROM), including several instructions to make a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of this application.

The embodiments of the present application have been described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific embodiments, which are merely illustrative rather than restrictive. Under the inspiration of this application, without departing from the scope of protection of the purpose of this application and the claims, many forms can be made, which all fall within the protection of this application.

Claims

An image processing method, comprising:

acquiring N images, wherein the N images are images captured by the image acquisition component at different focusing distances;

dividing each of the N images into M regions;

Get the pixel contrast value of each area of each image;

Determine the coordinate information of the target object in the target image according to the pixel contrast value, wherein the target image is an image in the N images;

Acquire the target object in the target image according to the coordinate information.
The method according to claim 1, wherein the determining the coordinate information of the target object in the target image according to the pixel contrast value comprises:

According to the change trend of the pixel contrast value and the change trend of the focus distance, classify the M areas to obtain a classification result;

According to the classification result, the coordinate information of the target object in the target image is determined.
The method according to claim 2, wherein the classification of the M regions according to the change trend of the pixel contrast value and the change trend of the focus distance to obtain a classification result, comprising:

Classifying the first area in the M areas as a background area, wherein the change trend of the pixel contrast value of the first area is the same as the change trend of the focus distance;

Classifying the second area in the M areas as a foreground area, wherein the change trend of the pixel contrast value of the second area is opposite to the change trend of the focus distance;

The third area in the M areas is classified as the main area, wherein the change trend of the pixel contrast value of the third area and the change trend of the focus distance are the same first and then opposite, or, the first The change trend of the pixel contrast value of the three regions and the change trend of the focus distance are opposite first and then the same;

Wherein, the target object includes: at least one of the background area, the foreground area and the main body area.
The method according to claim 1, wherein after acquiring the target object in the target image according to the coordinate information, the method further comprises:

display the target object in the fourth area of the screen;

Objects other than the target object in the target image are displayed in the fifth area of the screen.
The method according to claim 1, wherein the target image is an image with the target object as a focus among the N images.
An image processing device, comprising:

a first acquisition module, configured to acquire N images, wherein the N images are images captured by the image acquisition component at different focusing distances;

a dividing module, for dividing each of the N images into M regions;

The second acquisition module is used to acquire the pixel contrast value of each area of each image;

a determining module, configured to determine the coordinate information of the target object in the target image according to the pixel contrast value, wherein the target image is an image in the N images;

A third acquiring module, configured to acquire the target object in the target image according to the coordinate information.
The apparatus of claim 6, wherein the determining module comprises:

A classification submodule, configured to classify the M areas according to the change trend of the pixel contrast value and the change trend of the focus distance, and obtain a classification result;

A determination submodule, configured to determine the coordinate information of the target object in the target image according to the classification result.
The device according to claim 7, wherein the classification submodule is specifically used for:

Classifying the first area in the M areas as a background area, wherein the change trend of the pixel contrast value of the first area is the same as the change trend of the focus distance;

Classifying the second area in the M areas as a foreground area, wherein the change trend of the pixel contrast value of the second area is opposite to the change trend of the focus distance;

The third area in the M areas is classified as the main area, wherein the change trend of the pixel contrast value of the third area and the change trend of the focus distance are the same first and then opposite, or, the first The change trend of the pixel contrast value of the three regions and the change trend of the focus distance are opposite first and then the same;

Wherein, the target object includes: at least one of the background area, the foreground area and the main body area.
The apparatus of claim 6, wherein the apparatus further comprises:

The display module is configured to display the target object in the fourth area of the screen, and display other objects in the target image except the target object in the fifth area of the screen.
The apparatus according to claim 6, wherein the target image is an image of the N images with the target object as a focus.
An electronic device, comprising: a processor, a memory, and a program or instruction stored on the memory and executable on the processor, the program or instruction being executed by the processor to implement claims 1 to 5. The steps of any one of the image processing methods.
An electronic device configured to perform the steps of the image processing method as claimed in any one of claims 1 to 5.
A computer-readable storage medium storing programs or instructions on the computer-readable storage medium, when the programs or instructions are executed by a processor, the steps of the image processing method according to any one of claims 1 to 5 are implemented.
A computer program product executable by a processor to implement the steps of the image processing method according to any one of claims 1 to 5.
A chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or an instruction to implement the steps of the image processing method according to any one of claims 1 to 5 .