WO2021135945A1

WO2021135945A1 - Image processing method and apparatus, storage medium, and electronic device

Info

Publication number: WO2021135945A1
Application number: PCT/CN2020/136777
Authority: WO
Inventors: 金越
Original assignee: Oppo广东移动通信有限公司
Priority date: 2019-12-31
Filing date: 2020-12-16
Publication date: 2021-07-08
Also published as: CN111182212B; CN111182212A

Abstract

Embodiments of the present application disclose an image processing method and apparatus, a storage medium, and an electronic device. The method in the embodiments of the present application comprises: obtaining a preview image acquired by a camera; performing region division on the preview image, so as to obtain multiple regions of the preview image; evaluating the image quality of the multiple regions, so as to obtain multiple evaluation results; and determining a target region according to the multiple evaluation results, and performing photography using the target region as a central region.

Description

Image processing method, device, storage medium and electronic equipment

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office, the application number is 201911421569.4, and the application name is "Image processing methods, devices, storage media and electronic equipment" on December 31, 2019, the entire contents of which are incorporated by reference In this application.

Technical field

This application relates to the field of image processing technology, and in particular to an image processing method, device, storage medium, and electronic equipment.

Background technique

With the continuous development of the camera function of the smart terminal, the hardware technology level of the shooting component of the smart terminal is getting higher and higher, the pixels of the camera are also getting higher and higher, and the focusing function is getting more and more powerful. the part that can not be lost.

People take pictures through smart terminals, such as mobile phones, and share and upload the obtained photos to social networks via the Internet, which brings closer communication between people. Moreover, with the rise of the trend of showing photos on social platforms, users increasingly hope to take more beautiful and professional photos with their mobile phones.

Summary of the invention

The embodiments of the present application provide an image processing method, device, storage medium, and electronic equipment, which can accurately compose photographs and improve the quality of photographs.

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

Obtain the preview image collected by the camera;

Performing area division on the preview image to obtain multiple areas of the preview image;

Evaluating the image quality of the multiple regions to obtain multiple evaluation results;

The target area is determined according to the multiple evaluation results, and the target area is taken as the central area for shooting.

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

An acquiring unit for acquiring the preview image collected by the camera;

A dividing unit, configured to divide the preview image into regions to obtain multiple regions of the preview image;

An evaluation unit, configured to evaluate the image quality of the multiple regions to obtain multiple evaluation results;

The determining unit determines a target area according to the multiple evaluation results, and takes the target area as a central area for shooting.

In the third aspect, the storage medium provided by the embodiment of the present application has a computer program stored thereon, and when the computer program runs on a computer, the computer is caused to execute the image processing method provided in any embodiment of the present application.

In a fourth aspect, the electronic device provided by an embodiment of the present application includes a processor and a memory, the memory has a computer program, and the processor is used to execute the image provided by any embodiment of the present application by invoking the computer program. Approach.

Description of the drawings

The following detailed description of specific implementations of the present application in conjunction with the accompanying drawings will make the technical solutions and other beneficial effects of the present application obvious.

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

FIG. 2 is a schematic diagram of a scene of an image processing method provided by an embodiment of the application.

FIG. 3 is a schematic diagram of another scene of the image processing method provided by an embodiment of the application.

FIG. 4 is a schematic diagram of another flow of an image processing method provided by an embodiment of the application.

FIG. 5 is a schematic diagram of modules of an image processing device provided by an embodiment of the application.

FIG. 6 is a schematic structural diagram of an electronic device provided by an embodiment of the application.

FIG. 7 is a schematic diagram of another structure of an electronic device provided by an embodiment of the application.

Detailed ways

Please refer to the drawings, where the same component symbols represent the same components, and the principle of the present application is implemented in an appropriate computing environment for illustration. The following description is based on the exemplified specific embodiments of the application, which should not be regarded as limiting other specific embodiments of the application that are not described in detail herein.

The term "module" used in this article can be regarded as a software object executed on the computing system. The different components, modules, engines and services mentioned in this article can be regarded as the implementation objects on the computing system. The device and method described herein are preferably implemented in the form of software, of course, they can also be implemented on hardware, and they all fall within the protection scope of the present application.

An embodiment of the application provides an image processing method, including:

Obtain the preview image collected by the camera;

In an implementation manner, the region division of the preview image to obtain multiple regions of the preview image may include:

Determining the pixel value of the preview image;

The preview image is divided based on the pixel value of the preview image and the preset ratio to obtain multiple regions.

In an embodiment, the obtaining multiple regions may include:

Performing area marks on the multiple areas respectively, where the area marks are used to indicate the position of each area in the multiple areas;

A central area and a non-central area in the plurality of areas are determined based on the area marking result.

In an embodiment, the determining the target area according to the multiple evaluation results and taking the target area as the central area for shooting may include:

When the evaluation result of the central area is not less than the evaluation result of the non-central area, the central area is taken as the target area, and the preview image is taken as the target shooting image;

When the evaluation result of the central area is smaller than the evaluation result of the non-central area, the shooting angle of the camera is adjusted according to the positional relationship between the non-central area and the central area with the largest evaluation result.

In an embodiment, the adjusting the shooting angle of the camera according to the positional relationship between the non-central area and the central area with the largest evaluation result may include:

When the number of non-central regions with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central region with the largest evaluation result;

When the number of non-central regions with the largest evaluation result is two, determine whether the two non-central regions with the largest evaluation result have a common edge;

When there is a common edge, adjust the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results.

In an embodiment, the adjusting the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central area with the largest evaluation result may include:

Calculating the evaluation difference between the non-central area and the central area with the largest evaluation result;

Determining, according to the evaluation difference, an adjustment angle in the diagonal direction of the preview image corresponding to the non-central area with the largest evaluation result;

In response to the adjustment angle, the shooting angle of the camera is adjusted.

In an implementation manner, the adjusting the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results may include:

Calculate the evaluation difference between the two non-central areas with the largest evaluation results and the central area;

Determining the adjustment angles in the common side direction of the two non-central regions with the largest evaluation result according to the evaluation difference;

In an embodiment, the adjusting the shooting angle of the camera in response to the adjusting angle may include:

Generating prompt information according to the adjustment angle;

Guide the user to adjust the shooting angle of the camera based on the prompt information.

In an implementation manner, evaluating the image quality of the multiple regions to obtain multiple evaluation results may include:

Image quality scores are performed on the multiple regions based on the image quality assessment algorithm, and corresponding multiple assessment results are obtained.

The embodiment of the application provides an image processing method. The execution subject of the image processing method may be the image processing device provided in the embodiment of the application, or an electronic device integrated with the image processing device, wherein the image processing device may use hardware or Realized by software. Among them, the electronic device may be a smart phone, a tablet computer, a PDA (Personal Digital Assistant), etc.

The following is a specific analysis and description.

An embodiment of the application provides an image processing method. As shown in FIG. 1, FIG. 1 is a schematic flowchart of the image processing method provided by the embodiment of the application. The image processing method may include the following steps:

101. Obtain a preview image collected by the camera.

Wherein, the preview image refers to the image displayed in real time on the display of the electronic device after starting the camera. The electronic device can shoot in real time by calling the camera component, collect the current preview image, and display it on the display of the electronic device. In one embodiment, the shooting angle of the camera component can be adjusted, for example, the camera component can be controlled The shooting angle of the camera is adjusted upward, downward, left or right. After the shooting angle of the camera assembly is adjusted, the correspondingly captured preview image will also change with the adjustment of the shooting angle.

In one embodiment, the camera assembly includes a front camera and a rear camera, and the user can determine whether to use the front camera or the rear camera as needed.

102. Perform area division on the preview image to obtain multiple areas of the preview image.

Among them, dividing the preview image refers to dividing the real-time image screen displayed by the current electronic device into different areas according to certain rules. The divided areas can be disjoint pictures or overlapping pictures. For example, the preview image is divided into 5 areas according to the same ratio, namely upper left, upper right, lower right, lower left, and five areas in the center. There are overlapping pictures in the five areas.

In an embodiment, the step of dividing the preview image into regions to obtain multiple regions of the preview image may include:

(1) Determine the pixel value of the preview image;

(2) Divide the preview image based on the pixel value of the preview image and the preset ratio to obtain multiple regions.

Among them, the pixel value refers to the value assigned by the computer when the original image is digitized. It represents the average brightness information of a small square of the original, or the average reflection (transmission) density information of the small square. When converting a digital image into a halftone image, the dot area ratio (dot percentage) has a direct relationship with the pixel value (gray value) of the digital image, that is, the size of the dot represents the average brightness information of a small square of the original manuscript. .

Among them, the preset ratio refers to the ratio artificially set in the actual situation, for example, the preset ratio can be 1:0.8, that is, the ratio of 80% of the preview image can be taken according to the pixel value, and multiple images can be divided by this ratio area. For example, referring to the image 100 shown in FIG. 2, the image may be zoomed according to the center, upper left, upper right, lower left, and lower right directions to obtain multiple regions.

In an embodiment, the step of obtaining multiple regions may include:

(1) Perform area marks on the multiple areas respectively, and the area marks are used to indicate the position of each area in the multiple areas;

(2) Determine the central area and the non-central area of the plurality of areas based on the position.

Among them, the area marking refers to marking the divided area through the location words. For example, referring to FIG. 2, these five areas can be marked as 1 (upper left), 2 (upper right), 3 (lower right), 4 (lower left), and 5 (center).

103. Evaluate the image quality of multiple regions to obtain multiple evaluation results.

In one embodiment, the image quality of the multiple regions may be evaluated by an image quality evaluation algorithm, and the multiple regions may be scored respectively based on the image quality evaluation algorithm to obtain corresponding multiple evaluation results.

Among them, the image quality evaluation algorithm refers to the evaluation of the quality of the image by analyzing the characteristics of the image, and outputting a score for the current image quality. Among them, the characteristics include image composition, color matching, brightness, distortion, noise, etc. The higher the evaluation result obtained by the image quality evaluation algorithm, the better the image quality.

Among them, the image quality evaluation algorithm can be divided into subjective evaluation with reference and objective evaluation without reference in method. Subjective reference evaluation is to evaluate the quality of the image from the subjective perception of the person, and give the original reference image. The original reference image is the picture with the best image quality, and other pictures are scored based on this picture. Generally, the average subjective score (Mean Opinion Score, MOS) or the average subjective score difference (Differential Mean Opinion Score, DMOS) is used to express. The objective non-reference evaluation refers to the lack of the best reference picture, the mathematical model is trained, and the mathematical model is used to give the quantified value. Generally speaking, the image score is 1-10 points; 1 point represents poor image quality, and 10 points represent the image good quality. The score can be a discrete value or a continuous value.

Among them, objective non-reference evaluation can include two implementation methods, one is to use multiple models to evaluate the image quality; the other is to use one model to evaluate the quality. The method of using multiple models to evaluate image quality is to train multiple models, and each model is only responsible for evaluating one characteristic, such as composition, color matching, brightness, distortion, and noise. Take the weighted average of the scores output by each model to get the quality evaluation score of the whole picture. The method of using a single model to evaluate the quality of an image is to train only one model, be responsible for evaluating various factors at the same time, and directly output the quality score of the image, that is, the evaluation result.

In some embodiments, to perform quality assessment on an image, an image quality assessment model may be trained according to a deep learning algorithm such as CNN (Convolutional Neural Network), and the image quality assessment model may be performed according to the image quality assessment model. Among them, the image quality evaluation model generally includes an input layer, a hidden layer, and an output layer; the input layer is used to receive the input of the image; the hidden layer is used to process the received image; the output layer is used to output the final result of the image processing. The quality evaluation score of the output image. When the image quality evaluation scores are discrete, such as 1, 2, 3, ..., 10, a classification model can be used, and the output result is the confidence level of 10 classifications. The classification with the highest confidence can be used as the quality evaluation score of the image. When the image quality evaluation scores are continuous, such as 1, 1.1, 1.3,..., 9.5, 10, a regression model can be used, and the output result is a fraction with decimals. This result is the score of the image quality evaluation.

In some embodiments, the method of constructing training samples for image quality evaluation is as follows: multiple people score each image, and the average of these scores is taken as the quality evaluation label score of the current image. Because everyone has different scoring standards for pictures, for example, some people tend to score most images with an intermediate value of 5 or 6, and some people tend to expand the scoring distribution of images, and they think it is not good to score 1, 2 points. Score 8 or 9 points for images that you think are good. In order to eliminate the difference in scoring between people, you can count the distribution of each person's scoring on all images, and get the average and variance of each person's scoring; in this way, the score of each image can be adjusted.

104. Determine the target area according to multiple evaluation results, and take the target area as the central area for shooting.

In one embodiment, the evaluation results of all regions can be sorted, and then the evaluation results of the central region and the non-central region can be compared according to the ranking results, or the evaluation results of the central region and the non-central region can be directly compared. The judgment result is obtained according to the comparison result. After comparison, the area with the highest evaluation result is the target area.

In one embodiment, the location of the area can be distinguished by area marks, such as the aforementioned marks: 1 (upper left), 2 (upper right), 3 (lower right), 4 (lower left), 5 (center). For example, the non-central area is: 1, 2, 3, 4, and the central area is 5.

For example, when the target area is one, and the target area is the central area, such as the 5 areas in the image 100, the preview image can be directly used as the target captured image. For another example, when the target area is a non-central area, for example, the target area is area 1 in the image 100, adjust the camera's shooting angle to the diagonal position of the preview image corresponding to the area 1. The diagonal line is the diagonal line formed by the line connecting the upper left end point and the lower right end point of area 1 in the image 100. When there are two target areas, for example, when the target areas are area 1 and area 2 in the image 100, then adjust the camera's shooting angle upward in the direction of the common side of area 1 and area 2. At this time, the common The edge is the edge formed by connecting the upper left end point and the upper right end point of the image 100. It should be noted that adjusting the direction of the camera is the direction with a higher evaluation result.

In an embodiment, the step of determining the target area according to the multiple evaluation results and taking the target area as the central area for shooting may include:

(1) When the evaluation result of the central area is greater than or equal to the evaluation result of the non-central area, the central area is taken as the target area, and the preview image is taken as the target captured image;

(2) When the evaluation result of the central area is smaller than the evaluation result of the non-central area, the shooting angle of the camera is adjusted according to the position relationship between the non-central area and the central area with the largest evaluation result.

Among them, the shooting angle includes shooting height, shooting direction and shooting distance. The shooting height is divided into three types: horizontal shooting, overhead shooting and upward shooting. The shooting direction is divided into front angle, side angle, oblique angle, back angle, etc. The shooting distance is one of the elements that determines the scene.

In an embodiment, the step of adjusting the shooting angle of the camera according to the positional relationship between the non-central area and the central area with the largest evaluation result may include:

(1) When the number of non-central areas with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position corresponding to the non-central area with the largest evaluation result;

(2) When the number of non-central areas with the largest evaluation result is two, judge whether the two non-central areas with the largest evaluation results have a common edge. When there is a common edge, according to the two non-central areas with the largest evaluation results The positional relationship between the common edge and the central area of the camera adjusts the shooting angle of the camera.

It should be noted that there are many situations in which the evaluation results obtained from the multiple regions exist. In the actual adjustment of the camera angle, the angle adjustment can be performed in a corresponding manner according to different division rules.

In an embodiment, the step of adjusting the shooting angle of the camera to the diagonal position of the non-central area with the largest evaluation result may include:

(1) Calculate the evaluation difference between the non-central area with the largest evaluation result and the central area;

(2) Determine the adjustment angle in the diagonal direction corresponding to the non-central area with the largest evaluation result according to the evaluation difference;

(3) In response to the adjustment angle, the shooting angle of the camera is adjusted.

Among them, the evaluation difference refers to the difference between the evaluation result between the non-central area and the central area with the largest evaluation result. According to the evaluation difference, the parameter value of the adjustment angle can be determined, and the shooting angle of the camera can be adjusted correspondingly according to the parameter value.

In an embodiment, the step of adjusting the shooting angle of the camera according to the position relationship between the central area and the common edges of the two non-central areas with the largest evaluation results may include:

(4) Calculate the evaluation difference between the two non-central areas with the largest evaluation results and the central area;

(5) Determine the adjustment angle in the direction of the common side of the two non-central regions with the largest evaluation result according to the evaluation difference;

(6) In response to the adjustment angle, the shooting angle of the camera is adjusted.

In an embodiment, the step of adjusting the shooting angle of the camera according to the response to the adjustment angle may include:

(1) Generate prompt information according to the adjustment angle;

(2) Guide the user to adjust the shooting angle of the camera based on the prompt information.

For example, when a user uses a mobile phone to shoot a photographed person as shown in FIG. 3, after the mobile phone determines the shooting angle to be adjusted, prompt information may be generated according to the adjusted angle to guide the user. When the direction to move is determined, as shown in Figure 3, the prompt message can be: "Please move the phone horizontally upwards". When the user moves the camera, the camera's shooting angle is monitored at the same time. When the user's When the angle is adjusted properly, the prompt message can be: "The current image quality is good and you can shoot, please click the shutter". Among them, specific adjusted parameters can also be added to the prompt information.

It can be seen from the above that the embodiment of the present application obtains a preview image collected by a camera; divides the preview image into regions to obtain multiple regions of the preview image; evaluates the image quality of the multiple regions to obtain multiple evaluation results; The target area is determined according to the multiple evaluation results, and the target area is taken as the central area for shooting. In this way, through the quality evaluation of multiple regions after the preview image is divided, multiple evaluation results are obtained, and the most suitable target area for photographing is determined according to the evaluation results, and the target area is taken as the central area for shooting to achieve more Accurate shooting composition, improve shooting quality.

According to the method described in the foregoing embodiment, an example will be given below for further detailed description.

Please refer to FIG. 4, which is a schematic flowchart of another image processing method provided by an embodiment of the application.

Specifically, the method includes:

201. Obtain a preview image collected by a camera.

For example, the electronic device can shoot in real time by calling the camera component, collect the current preview image, and display it on the display of the electronic device. In one embodiment, the shooting angle of the camera component can be adjusted, for example, the camera component can be controlled. The shooting angle of the camera assembly is adjusted up, down, left or right. After the shooting angle of the camera assembly is adjusted, the correspondingly captured preview image will also change with the adjustment of the shooting angle. Among them, the camera component may include a front camera and a rear camera, and the user can determine whether to use the front camera or the rear camera as needed.

202. Determine the pixel value of the preview image.

Among them, the pixel value refers to the value assigned by the computer when the original image is digitized, and it represents the average brightness information of a small square of the original. In one embodiment, the average brightness information of the preview image may be calculated to facilitate subsequent division of the preview image based on the brightness information.

203. Divide the preview image based on the pixel value of the preview image and the preset ratio to obtain multiple regions.

For example, referring to the image 100 shown in FIG. 2, the image can be zoomed according to the upper left, upper right, lower right, lower left, and center directions, and the corresponding average brightness information is taken to obtain multiple regions. Further, the preview image can be divided with a preset ratio of 1:0.8, and the preview image can be divided into five areas, namely, the upper left area, the upper right area, the lower right area, the lower left area, and the center area. There are overlapping screens in each area. Each divided area is a rectangle with the same width and height ratio as the original image, and the size is 80% of the original image, which ensures that the result of the image quality evaluation is comparable to the result of the original image. And taking 80% of the original image can ensure that the image after the division does not lose too much global information, and there are obvious differences between the images after the division. Take the upper left, upper right, lower left, and lower right areas to simulate the image quality at the center of the viewfinder frame when the camera is moved to these four positions.

204. Perform area marks on the multiple areas respectively, where the area marks are used to indicate the position of each area in the multiple areas.

For example, these five areas can be denoted as: 1 (top left), 2 (top right), 3 (bottom right), 4 (bottom left), and 5 (center). Each mark indicates the location of each area.

205. Determine a central area and a non-central area in the multiple areas based on the area marking result.

For example, the non-central area is: 1, 2, 3, 4, and the central area is 5.

206. Evaluate images in multiple regions based on an image quality evaluation algorithm to obtain multiple evaluation results.

For example, as shown in Figure 2, the image quality evaluation algorithm can be used to evaluate the quality of the five regions of the current frame, and output five scores.

207. Determine whether the evaluation result of the central area is less than the evaluation result of the non-central area.

Wherein, when the evaluation result of the central area is less than the evaluation result of the non-central area, step 209 is executed; when the evaluation result of the central area is not less than the evaluation result of the non-central area, step 208 is executed.

In one embodiment, the evaluation results of all regions can be sorted, and then the evaluation results of the central region and the non-central region can be compared according to the ranking results, or the evaluation results of the central region and the non-central region can be directly compared. According to the comparison result, the judgment result of step 207 is obtained.

208. Use the central area as the target area and use the preview image as the target captured image.

For example, the image 100 can be referred to, that is, the score of the area 5 is not less than the score of any other four areas, and the preview image is taken as the target image.

Among them, after comparing the evaluation results of each area, the area with the highest evaluation result is the target area.

209. Determine whether the non-central area with the largest evaluation result is single.

Wherein, when the non-central area with the largest evaluation result is single, step 210 is executed; when the non-central area with the largest evaluation result is not single, step 211 is executed.

210. Adjust the shooting angle of the camera to the diagonal position corresponding to the non-central area with the largest evaluation result.

In one embodiment, the evaluation difference between the non-central area with the largest evaluation result and the evaluation result of the central area can be calculated, and then the diagonal direction of the non-central area with the largest evaluation result can be determined according to the evaluation difference. The adjustment angle. In response to the adjustment angle, the electronic device adjusts the shooting angle of the camera.

For example, in the reference image 100, when one of the evaluation results of the four

regions

1, 2, 3, and 4 is greater than the other three, it moves to the diagonal direction of the preview image corresponding to the region with the largest evaluation result. For example, if the evaluation result of area 1 is the largest, it moves along the diagonal line formed by the line connecting the upper left end point and the lower right end point of area 1 in the image 100, and the moving direction is the direction where area 1 is located, that is, the upper left direction.

211. Determine whether there is a common edge between non-central areas.

If the judgment result of step 210 is "Yes", then directly jump to step 212; if the judgment result of step 210 is "No", return to step 201 and restart image detection.

For example, if

areas

1 and 4 have the highest scores, and they do not have a common edge, they do not move, and wait for the next frame of detection, that is, re-detect the next frame of preview image. All in all, adjust the camera angle in the direction where the evaluation value is larger.

212. Adjust the shooting angle of the camera according to the positional relationship between the common edge between the non-central area and the central area with the largest evaluation result.

For example, when the number of non-central regions with the largest evaluation result is two, the shooting angle of the camera is adjusted according to the positional relationship between the common side of the two non-central regions with the largest evaluation result and the central region.

Wherein, the positional relationship between the non-central area and the central area can be determined by setting a position reference standard. For example, the diagonal line and each side of the preview image represented by the image 100 can be used as the position reference standard. For example, the evaluation difference between the two non-central areas with the largest evaluation results and the central area can be calculated, and then the adjustment angles in the common side direction of the two non-central areas with the largest evaluation results can be determined according to the evaluation differences. In response to the adjustment angle, the electronic device adjusts the shooting angle of the camera.

In some embodiments, the direction of the most frequent occurrence in the area mark can be used as a reference to determine the direction of the camera movement, and the direction of the most frequent occurrence represents the direction of the camera adjustment. For example, with reference to image 100, if the highest score is 1, 2, and the direction with the most occurrences is "up", that is, the common side with the upper common side moves upward. All in all, adjust the camera angle in the direction where the evaluation value is larger.

The adjustment of the shooting angle of the camera may be to automatically adjust the focus direction of the camera, or to generate prompt information by adjusting the angle, and then guide the photographer to adjust the shooting angle of the camera according to the prompt information.

213. Take pictures.

That is, after the above-mentioned adjustment of the shooting angle of the camera, the target shooting image can be determined and the shooting can be carried out. In one embodiment, the shooting behavior may be triggered by the user by pressing the physical shutter button on the electronic device, or by the user touching the virtual shutter control on the display interface of the electronic device, or the electronic device may detect the preview image. It was taken automatically when the image was taken for the target.

In order to facilitate better implementation of the image processing method provided in the embodiment of the present application, the embodiment of the present application also provides an image processing apparatus based on the foregoing. The meaning of the nouns is the same as in the above image processing method, and the specific implementation details can refer to the description in the method embodiment.

Please refer to FIG. 5. FIG. 5 is a schematic diagram of modules of an image processing apparatus provided by an embodiment of the application. Specifically, the image processing device 300 includes: an acquisition unit 31, a division unit 32, an evaluation unit 33, and a determination unit 34.

The acquiring unit 31 is configured to acquire a preview image collected by the camera.

Wherein, the preview image refers to the image displayed in real time on the display of the electronic device after starting the camera. The electronic device can shoot in real time by calling the camera component, and the acquisition unit 31 collects the current preview image and displays it on the display of the electronic device.

The dividing unit 32 is configured to divide the preview image into regions to obtain multiple regions of the preview image.

In one embodiment, the dividing unit 32 is configured to determine the pixel value of the preview image, and then divide the preview image based on the pixel value of the preview image and a preset ratio to obtain multiple regions.

In one embodiment, it is also used to determine the pixel value of the preview image, and then divide the preview image based on the pixel value of the preview image and a preset ratio to obtain multiple regions. Mark the multiple areas separately, the area mark is used to indicate the position of each area in the multiple areas; the central area and the non-central area in the multiple areas are determined based on the result of the area marking.

The evaluation unit 33 is used to evaluate the image quality of the multiple regions to obtain multiple evaluation results.

In one embodiment, the evaluation unit 33 may be specifically configured to score the image quality of multiple regions based on an image quality evaluation algorithm to obtain corresponding multiple evaluation results.

The determining unit 34 is configured to determine a target area according to the multiple evaluation results, and take the target area as a central area for shooting.

In one embodiment, the determining unit 34 is configured to, when the evaluation result of the central area is not less than the evaluation result of the non-central area, take the central area as the target area and use the preview image as the target captured image; when the evaluation result of the central area is When the evaluation result is smaller than the non-central area, the shooting angle of the camera is adjusted according to the position relationship between the non-central area with the largest evaluation result and the central area.

In one embodiment, the determining unit 34 is further configured to, when the evaluation result of the central area is not less than the evaluation result of the non-central area, use the central area as the target area and the preview image as the target captured image; when the evaluation result of the central area is When the result is less than the evaluation result of the non-central area, and when the number of non-central areas with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central area with the largest evaluation result; The electronic device calculates the evaluation difference between the non-central area with the largest evaluation result and the central area, and then, according to the evaluation difference, determines the diagonal adjustment angle of the preview image corresponding to the non-central area with the largest evaluation result . In response to the adjustment angle, the electronic device adjusts the shooting angle of the camera. When the evaluation result of the central area is less than the evaluation result of the non-central area and when the number of non-central areas with the largest evaluation result is two, judge whether the two non-central areas with the largest evaluation results have a common edge, when there is a common edge , Adjust the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results. The electronic device calculates the evaluation difference between the two non-central areas with the largest evaluation results and the central area, and then determines the adjustment angle in the common side direction of the two non-central areas with the largest evaluation results based on the evaluation difference. In response to the adjustment angle, the electronic device adjusts the shooting angle of the camera.

It can be seen from the foregoing that an embodiment of the present application provides an image processing device 300, which acquires a preview image collected by a camera through an acquisition unit 31; a division unit 32 divides the preview image into regions to obtain multiple regions of the preview image; an evaluation unit 33 evaluates the image quality of the multiple areas to obtain multiple evaluation results; the determining unit 34 determines the target area according to the multiple evaluation results, and takes the target area as the central area for shooting. In this way, through the quality evaluation of multiple regions after the preview image is divided, multiple evaluation results are obtained, and the most suitable target area for photographing is determined according to the evaluation results, and the target area is taken as the central area for shooting to achieve more Accurate shooting composition, improve shooting quality.

The embodiment of the present application also provides an electronic device. Please refer to FIG. 6, the electronic device 500 includes a processor 501 and a memory 502. Wherein, the processor 501 and the memory 502 are electrically connected.

The processor 500 is the control center of the electronic device 500. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes by running or loading a computer program stored in the memory 502, and calling data stored in the memory 502. Various functions of the electronic device 500 and data are processed, so as to monitor the electronic device 500 as a whole.

The memory 502 may be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the computer programs and modules stored in the memory 502. The memory 502 may mainly include a storage program area and a storage data area. The storage program area may store an operating system, a computer program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; Data created by the use of electronic equipment, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 502 may further include a memory controller to provide the processor 501 with access to the memory 502.

In the embodiment of the present application, the processor 501 in the electronic device 500 will load the instructions corresponding to the process of one or more computer programs into the memory 502 according to the following steps, and run the instructions by the processor 501 and store them in the memory 502. In order to realize various functions in the computer program, as follows:

Obtain the preview image collected by the camera;

Evaluate the image quality of the multiple regions to obtain multiple evaluation results;

In some embodiments, when the target area is determined according to the multiple evaluation results, and the target area is taken as the central area for shooting, the processor 501 may specifically execute the following steps:

When the evaluation result of the central area is not less than or equal to the evaluation result of the non-central area, the central area is taken as the target area, and the preview image is taken as the target captured image;

In some embodiments, when adjusting the shooting angle of the camera according to the positional relationship between the non-central area and the central area with the largest evaluation result, the processor 501 may specifically perform the following steps:

When the number of non-central areas with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central area with the largest evaluation result;

When the number of non-central regions with the largest evaluation result is two, judge whether the two non-central regions with the largest evaluation results have a common edge,

In some embodiments, the processor 501 may specifically perform the following steps when adjusting the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results:

Calculate the evaluation difference between the non-central area with the largest evaluation result and the central area;

Determine the diagonal adjustment angle of the preview image corresponding to the non-central area with the largest evaluation result according to the evaluation difference;

In some embodiments, when adjusting the shooting angle of the camera according to the positional relationship between the central area and the common edge of the two non-central areas with the largest evaluation results, the processor 501 may specifically perform the following steps:

The shooting angle of the camera is adjusted according to the positional relationship between the central area and the common edges of the two non-central areas with the largest evaluation results.

In some implementation manners, when the preview image is divided into regions to obtain multiple regions of the preview image, the processor 501 may specifically perform the following steps:

Determine the pixel value of the preview image;

In some embodiments, when multiple regions are obtained, the following steps may be included:

Based on the position, the central area and the non-central area of the plurality of areas are determined.

In some embodiments, when the image quality of the multiple regions is evaluated and multiple evaluation results are obtained, the processor 501 may specifically execute the following steps:

Image quality scores are performed on the multiple regions based on the image quality evaluation algorithm, and multiple corresponding evaluation results are obtained.

Please also refer to FIG. 7. In some embodiments, the electronic device 500 may further include a display 503, a radio frequency circuit 504, an audio circuit 505, and a power supply 506. Among them, the display 503, the radio frequency circuit 504, the audio circuit 505, and the power supply 506 are electrically connected to the processor 501, respectively.

The display 503 may be used to display information input by the user or information provided to the user, and various graphical user interfaces. These graphical user interfaces may be composed of graphics, text, icons, videos, and any combination thereof. The display 503 may include a display panel. In some embodiments, the display panel may be configured in the form of a liquid crystal display (LCD) or an organic light-emitting diode (OLED).

The radio frequency circuit 504 can be used to transmit and receive radio frequency signals to establish wireless communication with network equipment or other electronic equipment through wireless communication, and to transmit and receive signals with the network equipment or other electronic equipment.

The audio circuit 505 can be used to provide an audio interface between the user and the electronic device through a speaker or a microphone.

The power supply 506 can be used to supply power to various components of the electronic device 500. In some embodiments, the power supply 506 may be logically connected to the processor 501 through a power management system, so that functions such as charging, discharging, and power consumption management can be managed through the power management system.

Although not shown in FIG. 7, the electronic device 500 may also include a camera, a Bluetooth module, etc., which will not be repeated here.

The embodiments of the present application also provide a storage medium that stores a computer program, and when the computer program is run on a computer, the computer is caused to execute the image processing method in any of the above embodiments, such as: acquiring data collected by a camera. Preview image; divide the preview image to obtain multiple areas of the preview image; evaluate the image quality of the multiple areas to obtain multiple evaluation results; determine the target area according to the multiple evaluation results, and use the The target area is taken as the center area for shooting.

In the embodiment of the present application, the storage medium may be a magnetic disk, an optical disk, a read only memory (Read Only Memory, ROM), or a random access memory (Random Access Memory, RAM), etc.

In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.

It should be noted that for the image processing method of the embodiment of the present application, ordinary testers in the field can understand that all or part of the process of implementing the image processing method of the embodiment of the present application can be completed by controlling the relevant hardware through a computer program. The computer program can be stored in a computer readable storage medium, such as stored in the memory of an electronic device, and executed by at least one processor in the electronic device, and the execution process can include, for example, the implementation of an image processing method Example process. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, and the like.

For the image processing apparatus of the embodiment of the present application, its functional modules may be integrated into one processing chip, or each module may exist alone physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules. If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium, such as a read-only memory, a magnetic disk, or an optical disk.

The above describes in detail an image processing method, device, storage medium, and electronic equipment provided by the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation of the present application. The description of the above embodiments is only It is used to help understand the method and core idea of this application; at the same time, for those skilled in the art, according to the idea of this application, there will be changes in the specific implementation and the scope of application. In summary, this specification The content should not be construed as a limitation on this application.

Claims

An image processing method, which includes:

Obtain the preview image collected by the camera;

Performing area division on the preview image to obtain multiple areas of the preview image;

Evaluating the image quality of the multiple regions to obtain multiple evaluation results;

The target area is determined according to the multiple evaluation results, and the target area is taken as the central area for shooting.
The method according to claim 1, wherein said dividing the preview image into regions to obtain multiple regions of the preview image comprises:

Determining the pixel value of the preview image;

The preview image is divided based on the pixel value of the preview image and the preset ratio to obtain multiple regions.
The method according to claim 2, wherein said obtaining a plurality of regions comprises:

Performing area marks on the multiple areas respectively, where the area marks are used to indicate the position of each area in the multiple areas;

A central area and a non-central area in the plurality of areas are determined based on the area marking result.
The method according to claim 1, wherein the determining a target area according to the multiple evaluation results and taking the target area as a central area for shooting comprises:

When the evaluation result of the central area is not less than the evaluation result of the non-central area, the central area is taken as the target area, and the preview image is taken as the target shooting image;

When the evaluation result of the central area is smaller than the evaluation result of the non-central area, the shooting angle of the camera is adjusted according to the positional relationship between the non-central area and the central area with the largest evaluation result.
The method according to claim 4, wherein the adjusting the shooting angle of the camera according to the positional relationship between the non-central area and the central area with the largest evaluation result comprises:

When the number of non-central regions with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central region with the largest evaluation result;

When the number of non-central regions with the largest evaluation result is two, determine whether the two non-central regions with the largest evaluation result have a common edge;

When there is a common edge, adjust the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results.
The method according to claim 5, wherein the adjusting the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central area with the largest evaluation result comprises:

Calculating the evaluation difference between the non-central area and the central area with the largest evaluation result;

Determining, according to the evaluation difference, an adjustment angle in the diagonal direction of the preview image corresponding to the non-central area with the largest evaluation result;

In response to the adjustment angle, the shooting angle of the camera is adjusted.
The method according to claim 5, wherein the adjusting the shooting angle of the camera according to the positional relationship between the common side of the non-central area and the central area of the two largest evaluation results comprises:

Calculate the evaluation difference between the two non-central areas with the largest evaluation results and the central area;

Determining the adjustment angles in the common side direction of the two non-central regions with the largest evaluation result according to the evaluation difference;

In response to the adjustment angle, the shooting angle of the camera is adjusted.
The method according to claim 6, wherein the adjusting the shooting angle of the camera in response to the adjusting angle comprises:

Generating prompt information according to the adjustment angle;

Guide the user to adjust the shooting angle of the camera based on the prompt information.
The method according to claim 1, wherein evaluating the image quality of the plurality of regions to obtain a plurality of evaluation results comprises:

Image quality scores are performed on the multiple regions based on the image quality assessment algorithm, and corresponding multiple assessment results are obtained.
An image processing device, which includes:

An acquiring unit for acquiring the preview image collected by the camera;

A dividing unit, configured to divide the preview image into regions to obtain multiple regions of the preview image;

An evaluation unit, configured to evaluate the image quality of the multiple regions to obtain multiple evaluation results;

The determining unit determines a target area according to the multiple evaluation results, and takes the target area as a central area for shooting.
A computer-readable storage medium, wherein the storage medium stores a plurality of instructions, and the instructions are suitable for loading by a processor to execute the claims to perform the steps in the image processing method of claim 1 .
An electronic device including a processor and a memory, the memory having a computer program, wherein the processor is configured to execute:

Obtain the preview image collected by the camera;

Performing area division on the preview image to obtain multiple areas of the preview image;

Evaluating the image quality of the multiple regions to obtain multiple evaluation results;

The target area is determined according to the multiple evaluation results, and the target area is taken as the central area for shooting.
The electronic device according to claim 12, wherein the processor is configured to execute:

Determining the pixel value of the preview image;

The preview image is divided based on the pixel value of the preview image and the preset ratio to obtain multiple regions.
The electronic device according to claim 13, wherein the processor is configured to execute:

Performing area marks on the multiple areas respectively, where the area marks are used to indicate the position of each area in the multiple areas;

A central area and a non-central area in the plurality of areas are determined based on the area marking result.
The electronic device according to claim 12, wherein the processor is configured to execute:

When the evaluation result of the central area is not less than the evaluation result of the non-central area, the central area is taken as the target area, and the preview image is taken as the target shooting image;

When the evaluation result of the central area is smaller than the evaluation result of the non-central area, the shooting angle of the camera is adjusted according to the positional relationship between the non-central area and the central area with the largest evaluation result.
The electronic device according to claim 15, wherein the processor is configured to execute:

When the number of non-central regions with the largest evaluation result is single, adjust the shooting angle of the camera to the diagonal position of the preview image corresponding to the non-central region with the largest evaluation result;

When the number of non-central regions with the largest evaluation result is two, determine whether the two non-central regions with the largest evaluation result have a common edge;

When there is a common edge, adjust the shooting angle of the camera according to the positional relationship between the common edge of the non-central area and the central area of the two largest evaluation results.
The electronic device according to claim 16, wherein the processor is configured to execute:

Calculating the evaluation difference between the non-central area and the central area with the largest evaluation result;

Determining, according to the evaluation difference, an adjustment angle in the diagonal direction of the preview image corresponding to the non-central area with the largest evaluation result;

In response to the adjustment angle, the shooting angle of the camera is adjusted.
The electronic device according to claim 16, wherein the processor is configured to execute:

Calculate the evaluation difference between the two non-central areas with the largest evaluation results and the central area;

Determining the adjustment angles in the common side direction of the two non-central regions with the largest evaluation result according to the evaluation difference;

In response to the adjustment angle, the shooting angle of the camera is adjusted.
The electronic device according to claim 17, wherein the processor is configured to execute:

Generating prompt information according to the adjustment angle;

Guide the user to adjust the shooting angle of the camera based on the prompt information.
The electronic device according to claim 12, wherein the processor is configured to execute:

Image quality scores are performed on the multiple regions based on the image quality assessment algorithm, and corresponding multiple assessment results are obtained.