WO2020097836A1

WO2020097836A1 - Image processing method and apparatus, and computer device and storage medium

Info

Publication number: WO2020097836A1
Application number: PCT/CN2018/115523
Authority: WO
Inventors: 陈岩
Original assignee: 深圳市欢太科技有限公司; Oppo广东移动通信有限公司
Priority date: 2018-11-15
Filing date: 2018-11-15
Publication date: 2020-05-22
Also published as: CN112703530B; CN112703530A

Abstract

An image processing method, comprising: acquiring an original image; performing first filtering processing on the original image to obtain a first filtered image, and performing second filtering processing on the original image to obtain a second filtered image, wherein the sharpness of the first filtered image is higher than the sharpness of the second filtered image; performing weaken processing on the first filtered image according to the second filtered image to obtain an intermediate image; and performing superimposition processing on the first filtered image and the intermediate image to obtain a target image.

Description

Image processing method, device, computer equipment and storage medium

Technical field

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

Background technique

With the development of computer technology, more and more image processing technologies have appeared. In the process of processing the image, the image noise can be removed. However, while removing noise from the image, details of the image can also be blurred.

Summary of the invention

Based on this, it is necessary to provide an image processing method, device, computer equipment, and storage medium that can improve the clarity of image details and parts in view of the above technical problems.

An image processing method, the method includes:

Get the original image;

Performing a first filtering process on the original image to obtain a first filtered image, and performing a second filtering process on the original image to obtain a second filtered image, wherein the clarity of the first filtered image is higher than that of the second Filter the clarity of the image;

Weaken the first filtered image according to the second filtered image to obtain an intermediate image;

Superimposing the first filtered image and the intermediate image to obtain a target image.

An image processing device including:

Acquisition module for acquiring original images;

A filtering processing module, configured to perform a first filtering process on the original image to obtain a first filtered image, and perform a second filtering process on the original image to obtain a second filtered image, wherein the clarity of the first filtered image Higher than the sharpness of the second filtered image;

A weakening processing module, configured to weaken the first filtered image according to the second filtered image to obtain an intermediate image;

The superimposition processing module is configured to superimpose the first filtered image and the intermediate image to obtain a target image.

A computer device includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to perform the following steps:

Get the original image;

A computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are realized: acquiring an original image;

The above image processing method, device, computer equipment and storage medium, after acquiring the original image, subject the original image to the first filtering process and the second filtering process to obtain the first filtered image and the second filtered image, respectively; A filtered image is weakened to obtain an intermediate image; finally, the intermediate image is superimposed on the first filtered image to obtain the target image. Performing the first filtering process and the second filtering process on the original image can remove the noise, and then superimpose the intermediate image on the first filtered image, which can enhance the details in the image and improve the accuracy of image processing.

BRIEF DESCRIPTION

In order to more clearly explain the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, without paying any creative work, other drawings can be obtained based on these drawings.

1 is a schematic diagram of the internal structure of an electronic device in an embodiment;

2 is a flowchart of an image processing method in an embodiment;

3 is a flowchart of a method for freezing a frozen application program in an embodiment;

4 is a flowchart of a filter processing method in an embodiment;

5 is a flowchart of a weakening processing method in an embodiment;

6 is a flowchart of a noise recognition method in an embodiment;

7 is a structural block diagram of an application program device according to an embodiment;

8 is a structural block diagram of an application program device according to an embodiment;

9 is a block diagram of a partial structure of a mobile phone related to an electronic device provided by an embodiment of the present application.

detailed description

In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be described in further detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

It can be understood that the terms “first”, “second”, etc. used in this application may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first filtered image may be referred to as the second filtered image, and similarly, the second filtered image may be referred to as the first filtered image. Both the first filtered image and the second filtered image are filtered images, but they are not the same filtered image.

As shown in FIG. 1, a schematic diagram of an internal structure of an electronic device is provided. The electronic device includes a processor, memory, and display screen connected by a system bus. Among them, the processor is used to provide computing and control capabilities to support the operation of the entire electronic device. The memory is used to store data, programs, and / or instruction codes, etc. At least one computer program is stored on the memory, and the computer program can be executed by the processor to implement the image processing method for electronic devices provided in the embodiments of the present application. The memory may include a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random-access memory (Random-Access-Memory, RAM). For example, in one embodiment, the memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The computer program can be executed by the processor to implement an image processing method provided by various embodiments of the present application. The internal memory provides a cached operating environment for the operating system and computer programs in the non-volatile storage medium. The display screen can be a touch screen, such as a capacitive screen or an electronic screen, used to display the interface information of the foreground application program, and can also be used to detect a touch operation acting on the display screen and generate corresponding instructions, such as the application of the front and background applications Switching instructions, etc.

Those skilled in the art may understand that the structure shown in FIG. 1 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the electronic device to which the solution of the present application is applied. The specific electronic device may It includes more or fewer components than shown in the figure, or some components are combined, or have a different component arrangement. For example, the electronic device further includes a network interface connected through a system bus. The network interface may be an Ethernet card or a wireless network card, etc., and is used to communicate with external electronic devices, for example, it may be used to communicate with a server.

2 is a flowchart of an image processing method in an embodiment. As shown in FIG. 2, the image processing method includes steps 202 to 208. among them:

Step 202: Obtain the original image.

Among them, the image refers to a picture with visual effects. There may be image noise in the image. Image noise refers to unnecessary or redundant interference information present in the image. The presence of image noise seriously affects the quality of the image, so the image needs to be processed to remove image noise and improve the image quality. Images can be files in multiple formats, such as JPEG (Joint Photographic Experts GROUP), GIF (Graphics Interchange Format), PNG (Portable Network Graphics) and other formats .

Step 204: Perform a first filtering process on the original image to obtain a first filtered image, and perform a second filtering process on the original image to obtain a second filtered image, where the clarity of the first filtered image is higher than that of the second filtered image .

Among them, filtering refers to the operation of filtering out the frequency of a specific band in the signal. Filtering can be divided into high-pass filtering, low-pass filtering, Gaussian filtering, joint bilateral filtering, etc., which is not limited here.

In one embodiment, the first filtering process may be a joint bilateral filtering process, that is, a process performed according to a joint bilateral filter. Correspondingly, the first filtered image may be an image obtained by joint bilateral filtering processing on the original image.

Specifically, the process of joint bilateral filtering on the original image is as follows: the distance and color of each pixel in the original image are weighted and smoothed, and the original image is averagely blurred to remove noise in the original image. And retain the high-frequency part of the original image, which is the detail part of the image.

In one embodiment, the second filtering process may be a Gaussian filtering process, that is, a process performed according to a Gaussian filter. Correspondingly, the second filtered image may be an image obtained by performing Gaussian filtering on the original image.

Specifically, the process of performing Gaussian filtering on the original image is as follows: obtaining the original pixel value of each pixel in the original image and obtaining the neighborhood of the pixel; according to the original pixel value of each pixel in the original image, The second pixel value of each pixel is calculated in the neighborhood of, and a second filtered image is generated according to the second pixel value of each pixel.

Among them, the image is divided into several small squares, each small square is a pixel. The pixel value refers to the average brightness information of each small square in the image. The neighborhood refers to adjacent areas. The neighborhood of a pixel refers to an adjacent area centered on the pixel.

Specifically, after obtaining the original pixel value of each pixel in the original image and obtaining the neighborhood of the pixel, within the neighborhood of each pixel, the average pixel value of each pixel is calculated, that is, the second pixel value, and each The average pixel value is used as the pixel value of each original pixel to form a second filtered image. In the second filtered image, the average pixel value of each pixel in the entire original image is blurred, thereby removing noise in the original image.

The first filtered image obtained after the first filtering process retains the high-frequency part of the original image, so the details of the details in the first filtered image are relatively clear, and removed according to the second filtered image obtained after the second filtering process The noise in the original image is reduced, and the high-frequency part is weakened accordingly. Therefore, the first filtered image obtained finally retains more detailed information than the second filtered image, that is, the sharpness of the first filtered image is higher than that of the second filtered image.

Step 206: Perform a weakening process on the first filtered image according to the second filtered image to obtain an intermediate image.

The weakening process refers to the process of weakening the information in the image. For example, the second filtered image can be subtracted from the first filtered image, then the information in the first filtered image is weakened. It is also possible to multiply the second filtered image by a certain ratio and then subtract the second filtered image after multiplying by a certain ratio based on the first filtered image, which is not limited to this.

In this embodiment, the first filtered image may be an image obtained by joint bilateral filtering processing, and the second filtered image may be an image obtained by Gaussian filtering processing. The clarity of the first filtered image is higher than the clarity of the second filtered image.

Specifically, the low-frequency portion of the first filtered image is similar to the low-frequency portion of the second filtered image, while the first filtered image retains the high-frequency portion of the original image, and the pixel values of the high-frequency portion of the second filtered image are The pixel values of the low frequency part are averaged. Therefore, the first filtered image is subtracted from the second filtered image to obtain an intermediate image, that is, the high-frequency part of the first filtered image.

Step 208: Superimpose the first filtered image and the intermediate image to obtain the target image.

Among them, the superimposition process refers to the process of fusing multiple images. For example, after adding image A and image B, the average value is obtained to obtain the superimposed image. It is also possible to fuse image A and image B according to different weights to obtain a superimposed image, which is not limited to this.

Specifically, the intermediate image, that is, the high-frequency part of the first filtered image is superimposed on the first filtered image to obtain the target image. The low-frequency part of the target image retains the low-frequency part of the first filtered image, while the high-frequency part of the target image has a higher definition than the first filtered image.

In the above image processing method, after acquiring the original image, the original image is subjected to first filtering processing and second filtering processing to obtain a first filtered image and a second filtered image respectively; the first filtered image is weakened according to the second filtered image, The intermediate image is obtained; finally, the intermediate image is superimposed on the first filtered image to obtain the target image. In the above image processing method, the original image is subjected to the first filtering process and the second filtering process to remove noise, and then the intermediate image is superimposed on the first filtered image, which can enhance the details in the image and improve the accuracy of image processing Sex.

In one embodiment, as shown in FIG. 3, the step of acquiring the original image includes:

In step 302, when an image acquisition instruction is detected, the resource occupancy rate of the electronic device is acquired.

Among them, resources refer to the software or hardware resources that the electronic device must use when processing application events, such as the electronic device CPU (Central Processing Unit, central processing unit), memory (Memory), hardware, network resources, IO (Input -Output, input and output), etc. Resource occupancy rate refers to the proportion of resources occupied by electronic devices, generally refers to the ratio of occupied resources to all resources, which can be expressed as a percentage. For example, the total memory of the device is 128GB, and the already occupied memory is 56GB, then the resource occupancy rate of the device can be expressed as the memory occupancy rate, and the obtained memory occupancy rate is 43.75%.

Specifically, the image acquisition instruction may include information such as the size of the image, the address of the image, the resolution of the image, and the sharpness of the image. When the electronic device processes the image, it needs to occupy part of the software or hardware resources. Therefore, when the image acquisition instruction is detected, the resource occupancy rate of the electronic device is acquired.

Step 304: When the resource occupancy rate of the electronic device is greater than the occupancy rate threshold, acquire the target priority corresponding to the target application program that initiated the image acquisition instruction.

Among them, the priority refers to the priority level, that is, the degree of importance. When the priority of the application is higher, it means that the importance of the application is more important.

Specifically, when an application sends an image to an electronic device, it will initiate an image acquisition instruction. For the application programs in the electronic device, the priority corresponding to each application program can be set in advance. After the electronic device detects the image acquisition instruction, when the resource occupancy rate of the electronic device is greater than the occupancy threshold, the target application program that initiated the image acquisition instruction is acquired, and the target priority of the target application program is further acquired.

Further, when the resource occupancy rate of the electronic device is less than the occupancy rate threshold, the step of acquiring the original image is performed to process the original image.

Step 306: Obtain the frozen application from the applications running in the electronic device according to the target priority, and freeze the frozen application.

Among them, the running application can be frozen. The application program in the frozen state does not occupy processor resources to run, but still consumes resources such as memory and hardware of the electronic device. The application in the frozen state has not been closed, but it is not running temporarily.

Specifically, after acquiring the target priority of the target application, the application running in the electronic device is acquired according to the target priority, and then the frozen application is obtained from the running application, and the frozen application is frozen.

Step 308: Acquire the original image according to the image acquisition instruction.

Specifically, the image acquisition instruction may include the address of the image and the like. Acquire the address of the image according to the image acquisition instruction, so as to acquire the original image in the storage space corresponding to the address of the image. The original image can also be acquired in real time, and can also be acquired in other ways, not limited to this. For example, an image acquisition instruction is detected, and the camera is turned on to obtain the original image according to the image acquisition instruction.

In this embodiment, when an image acquisition instruction is detected, that is, before image processing, the resource occupancy rate of the electronic device is acquired, and when the resource occupancy rate is greater than the occupancy rate threshold, the electronic is acquired according to the target priority of the target application Freeze the application in the device and freeze the frozen application before acquiring the original image. After the application is frozen, more resources can be released to process the image by the electronic device, which can reduce the resource consumption of the electronic device.

In one embodiment, obtaining the frozen application from the application running in the electronic device according to the target priority includes: obtaining the priority threshold according to the resource occupancy rate and the target priority; obtaining from the application running in the electronic device Applications with a priority lower than the priority threshold are considered frozen applications.

Specifically, the occupancy threshold may include a first occupancy threshold and a second occupancy threshold, and the first occupancy threshold is less than the second occupancy threshold. When the resource occupancy rate is greater than the first occupancy threshold and less than the second occupancy threshold, the target priority is used as the priority threshold, and from the applications running in the electronic device, the application whose priority is lower than the priority threshold is obtained As a frozen application. When the resource occupancy rate is greater than or equal to the second occupancy threshold, the priority threshold is obtained according to the resource occupancy rate and the target priority. The priority threshold can be obtained by the following calculation formula: priority threshold = resource occupancy rate * k + target priority. Among them, k is a preset scale factor. It can be understood that the higher the resource occupancy rate, the fewer idle resources in the electronic device, and the more applications need to be frozen, that is, the higher the priority threshold.

For example, the first occupancy threshold is 80%, the second occupancy threshold is 90%, the resource occupancy of the electronic device is 90%, the target priority of the target application is 3, and the preset proportional coefficient k is 2. Then, the resource occupancy rate of the electronic device is equal to the second occupancy threshold 90%, and the priority threshold = resource occupancy rate * k + target priority = 90% * 2 + 3 = 4.8. Therefore, from the applications running in the electronic device, an application with a priority lower than the priority threshold of 4.8 is acquired as a frozen application.

In this embodiment, the priority threshold is obtained through the resource occupancy rate of the electronic device and the target priority of the target application, and from the applications running in the electronic device, the application with a priority lower than the priority threshold is obtained as a freeze The application program freezes the frozen application program and combines the resource occupancy rate of the electronic device and the target priority of the target application program to freeze the frozen application program, which can more accurately reduce the resource consumption of the electronic device.

In one embodiment, as shown in FIG. 4, performing a first filtering process on the original image to obtain a first filtered image, and performing a second filtering process on the original image to obtain a second filtered image includes:

Step 402: Obtain the brightness of the original image.

Wherein, the brightness of the original image refers to the brightness of the original image, which can usually be measured from a percentage of 0% (black) to 100% (white). The higher the percentage, the higher the brightness of the original image. The brightness of the original image may be calculated according to the pixel value of the pixel, or may be calculated according to other methods, which is not limited herein.

For example, if the original image is in RGB (Red Green, Blue, Red, Green, Blue) format, the brightness Y of the original image can be calculated by the following formula: Y = 0.299 * R + 0.587 * G + 0.114 * B. Where R represents the average value of the red channel pixel values of all pixels in the original image, G represents the average value of the green channel pixel values of all pixels in the original image, and B represents the average of the blue channel pixel values of all pixels in the original image . The brightness of the original image may be changed according to the change in the degree of exposure when taking a picture, or may be changed according to the change in the color depth of the image, which is not limited thereto.

Step 404: When the brightness of the original image is within the preset brightness range, acquire the first filtering parameter and the second filtering parameter.

The first filtering parameter refers to the filtering parameter of the first filtering process. The second filter parameter refers to the filter parameter of the second filter process.

Specifically, when the brightness of the original image is within the preset brightness range, the first filter parameter of the first filter process and the second filter parameter of the second filter process are acquired. The first filter parameter and the second filter parameter may be set in advance, or may be adjusted according to the brightness of the original image or other factors, which is not limited herein.

Further, when the brightness of the original image is less than the first brightness threshold, or when the brightness of the original image is greater than the second brightness threshold, the prompt information may be output through the electronic device. The first brightness threshold is greater than the second brightness threshold. The output of the prompt information through the electronic device may be the output of the brightness value of the original image and the output of the prompt message, such as "the image is too bright, and processing is not recommended."

Specifically, when the image is too bright or too dark, there is less available information in the image, so the image is not processed to avoid serious distortion of the image.

Step 406: Perform a first filtering process on the original image according to the first filtering parameter to obtain a first filtered image, and perform a second filtering process on the original image according to the second filtering parameter to obtain a second filtered image.

Specifically, after acquiring the first filtering parameter and the second filtering parameter, the electronic device performs first filtering processing and second filtering processing on the original image to obtain the first filtered image and the second filtered image, respectively. In this embodiment, the first filtering process may be a joint bilateral filtering process; the second filtering process may be a Gaussian filtering process. Accordingly, the first filtering parameter may be a joint bilateral filtering parameter; the second filtering parameter may be a Gaussian filtering parameter.

In this embodiment, when the brightness of the acquired original image is within the preset brightness range, the first filtering parameter and the second filtering parameter are acquired, and the original image is processed according to the first filtering parameter and the second filtering parameter, thereby avoiding Processing the original image that does not meet the preset brightness range saves the resources of the electronic device.

In one embodiment, as shown in FIG. 5, the first filtered image is weakened according to the second filtered image to obtain an intermediate image, including:

In step 502, the first filtered image is subtracted from the second filtered image to obtain a difference image.

Specifically, the flat portion in the first filtered image is similar to the flat portion in the second filtered image. The first filtered image retains the high-frequency part of the image, that is, the detail part of the image; the high-frequency part of the second filtered image is averaged by the low-frequency part in the neighborhood. The first filtered image is subtracted from the second filtered image to obtain a difference image, that is, a high-frequency part of the first filtered image, that is, a detail part in the first filtered image.

Step 504: Obtain the weighting factor of the difference image.

The weighting factor refers to a factor used to indicate the importance of the difference image in the target image.

Specifically, when the weighting factor of the difference image is larger, it indicates that the difference image is more important in the target image, that is, the detail part in the target image is clearer.

Further, the sharpness of the difference image is obtained; the weighting factor of the difference image is obtained according to the sharpness of the difference image.

Step 506: Obtain an intermediate image according to the difference image and the weighting factor of the difference image.

In this embodiment, the difference image may be multiplied by the weighting factor of the difference image to obtain an intermediate image, or the intermediate image may be obtained by other methods according to the weighting factor of the difference image and the difference image, which is not limited herein.

In this embodiment, the first filtered image is subtracted from the second filtered image to obtain a difference image, and then the weighting factor of the difference image is obtained, and the intermediate image can be obtained by the weighting factor of the difference image and the difference image, which can be more accurate To get the detail of the target image.

In one embodiment, obtaining the weighting factor of the difference image includes: obtaining the sharpness of the difference image; and obtaining the weighting factor of the difference image according to the sharpness of the difference image.

Among them, the clarity of the image refers to the clarity of the image.

Specifically, when the sharpness of the difference image is sufficiently high, the sharpness of the intermediate image obtained by increasing the weighting factor is not much different from the sharpness of the difference image, but consumes a lot of resources of the electronic device. Therefore, when the sharpness of the difference image is higher, it means that the high-frequency part of the difference image, that is, the higher the pixel value of the detail part, can reduce the weighting factor of the difference image. When the sharpness of the difference image is lower, it means that the high-frequency part of the difference image, that is, the lower the pixel value of the detail part, can increase the weighting factor of the difference image.

In this embodiment, the weighting factor of the difference image is obtained through the sharpness of the difference image. When the sharpness of the difference image is higher, the weighting factor can be reduced, so that the weight can be adjusted according to the sharpness of the difference image Factor to improve the accuracy of image processing.

In one embodiment, as shown in FIG. 6, after the first filtered image and the intermediate image are superimposed to obtain the target image, the method further includes:

Step 602: Identify the noise of the target image.

Among them, the noise of the image refers to unnecessary or unnecessary interference information existing in the image. The noise of the image will affect the accuracy of the image.

Specifically, the noise of the target image can be identified by the Filter-Based Approach Using Arithmetic Algorithm; the noise of the target image can also be identified by the Filter-Based Approach Using Statistics Averaging algorithm, or by identifying the noise in the target image, etc. Limited to this. Among them, the noise of the image is composed of various noises in the image. Pixels divide the image into several small squares, and the small squares that belong to noise are noises.

Step 604: Acquire the noise ratio of the noise in the target image.

Specifically, the noise ratio can be obtained through the ratio of the noise in the target image in the target image. If the resolution of the target image is 400 * 240, that is, the target image is divided into 400 * 240 pixels and the acquired noise is 100, then the noise ratio of the target image is 100/400 * 240 = 0.1%.

Step 606, when the noise ratio of the target image is greater than the ratio threshold, the target image is used as the original image, and the step of acquiring the original image is performed.

Specifically, when the noise ratio of the image is too large, the sharpness of the image is too low. When the noise ratio of the target image is greater than the ratio threshold, the target image is used as the original image, the step of acquiring the original image is performed, and the image processing is performed again to obtain the target image with a lower noise ratio. The ratio threshold may be set by the user in advance, or may be set in other ways, which is not limited herein.

In this embodiment, when the noise ratio of the target image is greater than the ratio threshold, the target image is used as the original image for image processing, and the target image with better denoising effect can be obtained.

It should be understood that although the steps in the flowcharts of FIGS. 2-6 are displayed in order according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless clearly stated in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least some of the steps in FIGS. 2-6 may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. The execution order of is not necessarily sequential, but may be executed in turn or alternately with at least a part of other steps or sub-steps or stages of other steps.

In one embodiment, the above image processing method may further include the following steps:

(1) When the image acquisition instruction is detected, the resource occupancy rate of the electronic device is acquired.

(2) When the resource occupancy rate of the electronic device is greater than the occupancy rate threshold, the target priority corresponding to the target application program that initiated the image acquisition instruction is acquired.

(3) Obtain the priority threshold according to the target priority and resource occupancy rate, obtain the frozen application from the application running in the electronic device, and freeze the application.

(4) Acquire the original image according to the image acquisition instruction.

(5) Freeze the frozen application, and after the electronic device releases some software or hardware resources, obtain the brightness of the original image.

(6) When the brightness of the original image is within a preset range, acquire the first filtering parameter and the second filtering parameter.

(7) Perform a first filtering process on the original image according to the first filtering parameter to obtain a first filtered image, and perform a second filtering process on the original image according to the second filtering parameter to obtain a second filtered image.

(8) The first filtered image is subtracted from the second filtered image to obtain a difference image.

(9) Acquiring the sharpness of the difference image.

(10) Obtain the weighting factor of the difference image according to the sharpness of the difference image.

(11) Obtain an intermediate image based on the weighting factor and the difference image.

(12) Superimpose the first filtered image and the intermediate image to obtain the target image.

(13) Identify the noise of the target image.

(14) Acquire the noise ratio of noise in the target image.

(15) When the noise ratio of the target image is greater than the ratio threshold, the target image is used as the original image, the step of acquiring the original image is performed, and the image processing is performed again.

In one embodiment, as shown in FIG. 7, an image processing apparatus 700 is provided, including: an acquisition module 702, a filter processing module 704, a weakening processing module 706, and an overlay processing module 708, wherein:

The obtaining module 702 is used to obtain the original image.

The filtering processing module 704 is configured to perform a first filtering process on the original image to obtain a first filtered image, and perform a second filtering process on the original image to obtain a second filtered image, where the clarity of the first filtered image is higher than that of the second filtered The clarity of the image.

The weakening processing module 706 is configured to weaken the first filtered image according to the second filtered image to obtain an intermediate image.

The superimposition processing module 708 is configured to superimpose the first filtered image and the intermediate image to obtain a target image.

The above image processing method, device, computer equipment and storage medium, after acquiring the original image, subject the original image to the first filtering process and the second filtering process to obtain the first filtered image and the second filtered image, respectively; A filtered image is weakened to obtain an intermediate image; finally, the intermediate image is superimposed on the first filtered image to obtain the target image. In the above image processing method, the original image is subjected to the first filtering process and the second filtering process to remove noise, and then the intermediate image is superimposed on the first filtered image to enhance the details in the image.

In one embodiment, as shown in FIG. 8, an image processing apparatus 800 is provided, including: a freezing module 802, an obtaining module 804, a filtering processing module 806, a weakening processing module 808, an overlay processing module 810, and a noise recognition module 812 ,among them:

The freezing module 802 is used to obtain the resource occupancy rate of the electronic device when an image acquisition instruction is detected; when the resource occupancy rate of the electronic device is greater than the occupancy threshold, obtain the target priority corresponding to the target application that initiated the image acquisition instruction ; Obtain the frozen application from the applications running in the electronic device according to the target priority, and freeze the frozen application. Acquiring the original image includes: acquiring the original image according to the image acquisition instruction.

The obtaining module 804 is used to obtain the original image.

The filtering processing module 806 is configured to perform a first filtering process on the original image to obtain a first filtered image, and perform a second filtering process on the original image to obtain a second filtered image, where the clarity of the first filtered image is higher than that of the second filtered The clarity of the image.

The weakening processing module 808 is configured to weaken the first filtered image according to the second filtered image to obtain an intermediate image.

The superimposition processing module 810 is configured to superimpose the first filtered image and the intermediate image to obtain a target image.

The noise recognition module 812 is used for recognizing the noise of the target image; acquiring the noise ratio of the noise in the target image; when the noise ratio of the target image is greater than the ratio threshold, taking the target image as the original image and performing the step of acquiring the original image.

For the above image processing method, device, computer equipment and storage medium, before acquiring the original image, when the resource occupancy rate of the electronic device is greater than the occupancy threshold, the frozen application is frozen, and then the original image is acquired; The first image filter and the second image filter can be used to remove the noise, and then the intermediate image can be superimposed on the first filtered image to enhance the detail in the image; when the noise ratio of the target image is greater than the ratio threshold, then Taking the target image as the original image and then performing image processing can reduce the power consumption of the electronic device while enhancing the detail of the target image.

In one embodiment, the above freezing module 802 is further used to obtain a priority threshold according to the resource occupancy rate and the target priority; from applications running in the electronic device, an application with a priority lower than the priority threshold is obtained as a frozen application program.

In one embodiment, the above filter processing module 806 is further used to obtain the brightness of the original image; when the brightness of the original image is within the preset brightness range, the first filter parameter and the second filter parameter are obtained; according to the first filter parameter pair The original image is subjected to a first filter process to obtain a first filtered image, and the second filter process is performed on the original image according to a second filter parameter to obtain a second filtered image.

In one embodiment, the aforementioned weakening processing module 808 is further used to subtract the first filtered image from the second filtered image to obtain a difference image; obtain a weighting factor of the difference image; according to the weighting factor of the difference image and the difference image Get the intermediate image.

In one embodiment, the above-mentioned weakening processing module 808 is further used to obtain the sharpness of the difference image; the weighting factor of the difference image is obtained according to the sharpness of the difference image.

The division of each module in the above image processing apparatus is for illustration only. In other embodiments, the image processing apparatus may be divided into different modules as needed to complete all or part of the functions of the above image processing apparatus.

For specific definitions of the image processing apparatus, reference may be made to the definition of the image processing method above, and details are not described herein again. Each module in the above image processing device may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in the hardware or independent of the processor in the computer device, or may be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

The implementation of each module in the image processing apparatus provided in the embodiments of the present application may be in the form of a computer program. The computer program can be run on a terminal or a server. The program module composed of the computer program may be stored in the memory of the terminal or the server. When the computer program is executed by the processor, the steps of the method described in the embodiments of the present application are implemented.

An embodiment of the present application also provides an electronic device. As shown in FIG. 9, for ease of description, only parts related to the embodiments of the present application are shown, and specific technical details are not disclosed, please refer to the method part of the embodiments of the present application. The electronic device may be any terminal device including a mobile phone, tablet computer, PDA (Personal Digital Assistant), POS (Point of Sales), in-vehicle computer, wearable device, etc. Taking the electronic device as a mobile phone for example :

9 is a block diagram of a partial structure of a mobile phone related to an electronic device provided by an embodiment of the present application. 9, the mobile phone includes: a radio frequency (Radio Frequency) circuit 910, a memory 920, an input unit 930, a display unit 940, a sensor 950, an audio circuit 960, a wireless fidelity (WiFi) module 970, a processor 980 , And power supply 990 and other components. Those skilled in the art may understand that the structure of the mobile phone shown in FIG. 9 does not constitute a limitation on the mobile phone, and may include more or less components than those shown in the figure, or a combination of certain components, or a different component arrangement.

Among them, the RF circuit 910 can be used to receive and send signals during the sending and receiving of information or during a call. It can receive the downlink information of the base station and process it to the processor 980; it can also send the uplink data to the base station. Generally, RF circuits include but are not limited to antennas, at least one amplifier, transceiver, coupler, low noise amplifier (Low Noise Amplifier, LNA), duplexer, and so on. In addition, the RF circuit 910 can also communicate with other devices through a wireless communication network. The above wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile (GSM), General Packet Radio Service (GPRS), and Code Division Multiple Access (Code Division) Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), e-mail, Short Message Service (SMS), etc.

The memory 920 may be used to store software programs and modules. The processor 980 executes various functional applications and data processing of the mobile phone by running the software programs and modules stored in the memory 920. The memory 920 may mainly include a program storage area and a data storage area, where the program storage area may store an operating system and at least one function-required application program (such as an application program for a sound playback function, an application program for an image playback function, etc.), etc .; The data storage area can store data (such as audio data, address book, etc.) created according to the use of the mobile phone. In addition, the memory 920 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.

The input unit 930 may be used to receive input numeric or character information, and generate key signal input related to user settings and function control of the mobile phone 900. Specifically, the input unit 930 may include a touch panel 931 and other input devices 932. The touch panel 931, also known as a touch screen, can collect user's touch operations on or near it (for example, the user uses any suitable objects or accessories such as fingers, stylus, etc. on or near the touch panel 931 Operation), and drive the corresponding connection device according to the preset program. In one embodiment, the touch panel 931 may include a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, and detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device and converts it into contact coordinates, and then sends It is given to the processor 980 and can receive the command sent by the processor 980 and execute it. In addition, the touch panel 931 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves. In addition to the touch panel 931, the input unit 930 may also include other input devices 932. Specifically, other input devices 932 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, switch keys, etc.), and the like.

The display unit 940 may be used to display information input by the user or information provided to the user and various menus of the mobile phone. The display unit 940 may include a display panel 941. In one embodiment, the display panel 941 may be configured in the form of a liquid crystal display (Liquid Crystal) (LCD), an organic light-emitting diode (Organic Light-Emitting Diode, OLED), or the like. In one embodiment, the touch panel 931 may cover the display panel 941, and when the touch panel 931 detects a touch operation on or near it, it is transmitted to the processor 980 to determine the type of touch event, and then the processor 980 according to The type of touch event provides a corresponding visual output on the display panel 941. Although in FIG. 9, the touch panel 931 and the display panel 941 are used as two independent components to realize the input and input functions of the mobile phone, in some embodiments, the touch panel 931 and the display panel 941 may be integrated and Realize the input and output functions of the mobile phone.

The mobile phone 900 may further include at least one sensor 950, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 941 according to the brightness of the ambient light, and the proximity sensor may close the display panel 941 and / or when the mobile phone moves to the ear Or backlight. The motion sensor may include an acceleration sensor. The acceleration sensor can detect the magnitude of acceleration in various directions, and can detect the magnitude and direction of gravity when at rest. It can be used for applications that recognize mobile phone gestures (such as horizontal and vertical screen switching), and vibration recognition related functions (such as Pedometer, percussion), etc. In addition, the mobile phone can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor and so on.

The audio circuit 960, the speaker 961, and the microphone 962 may provide an audio interface between the user and the mobile phone. The audio circuit 960 can transmit the converted electrical signal of the received audio data to the speaker 961, which converts the speaker 961 into a sound signal output; on the other hand, the microphone 962 converts the collected sound signal into an electrical signal, which After receiving, it is converted into audio data, and then processed by the audio data output processor 980, and then sent to another mobile phone through the RF circuit 910, or the audio data is output to the memory 920 for subsequent processing.

WiFi is a short-range wireless transmission technology. The mobile phone can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 970. It provides users with wireless broadband Internet access. Although FIG. 9 shows the WiFi module 970, it can be understood that it is not a necessary component of the mobile phone 900, and may be omitted as needed.

The processor 980 is the control center of the mobile phone, connects various parts of the entire mobile phone with various interfaces and lines, executes or executes the software programs and / or modules stored in the memory 920, and calls the data stored in the memory 920 to execute Various functions and processing data of the mobile phone, so as to monitor the mobile phone as a whole. In one embodiment, the processor 980 may include one or more processing units. In one embodiment, the processor 980 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, user interface, application programs, and the like; the modem processor mainly processes wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 980.

The mobile phone 900 further includes a power supply 990 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 980 through a power management system, so as to realize functions such as charging, discharging, and power management through the power management system.

In one embodiment, the mobile phone 900 may further include a camera, a Bluetooth module, and the like.

In the embodiment of the present application, the processor 980 included in the electronic device implements the steps of the image processing method when executing the computer program stored on the memory.

The embodiments of the present application also provide a computer-readable storage medium. One or more non-volatile computer-readable storage media containing computer-executable instructions, which when executed by one or more processors, cause the processors to perform the steps of the image processing method.

A computer program product containing instructions that, when run on a computer, causes the computer to perform an image processing method.

Any references to memory, storage, databases, or other media used in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR) SDRAM, enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The above-mentioned embodiments only express several implementation manners of the present application, and their descriptions are more specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which all fall within the protection scope of the present application. Therefore, the protection scope of the patent of this application shall be subject to the appended claims.

Claims

An image processing method, the method includes:

Get the original image;

Performing a first filtering process on the original image to obtain a first filtered image, and performing a second filtering process on the original image to obtain a second filtered image, wherein the clarity of the first filtered image is higher than that of the second Filter the clarity of the image;

Weaken the first filtered image according to the second filtered image to obtain an intermediate image;

Superimposing the first filtered image and the intermediate image to obtain a target image.
The method according to claim 1, wherein before acquiring the original image, the method further comprises:

When the image acquisition instruction is detected, the resource occupancy rate of the electronic device is acquired;

When the resource occupancy rate of the electronic device is greater than the occupancy rate threshold, acquire the target priority corresponding to the target application program that initiated the image acquisition instruction;

Obtaining a frozen application from the applications running in the electronic device according to the target priority, and freezing the frozen application;

The acquiring the original image includes:

Acquire the original image according to the image acquisition instruction.
The method according to claim 2, wherein the obtaining the frozen application from the applications running in the electronic device according to the target priority includes:

Obtaining a priority threshold according to the resource occupancy rate and the target priority;

From the applications running in the electronic device, an application with a priority lower than the priority threshold is obtained as a frozen application.
The method according to claim 1, wherein the first filtering process is performed on the original image to obtain a first filtered image, and the second filtering process is performed on the original image to obtain a second filtered image, including:

Obtain the brightness of the original image;

When the brightness of the original image is within a preset brightness range, acquire the first filtering parameter and the second filtering parameter;

Perform a first filtering process on the original image according to a first filtering parameter to obtain a first filtered image, and perform a second filtering process on the original image according to a second filtering parameter to obtain a second filtered image.
The method according to claim 1, wherein said weakening the first filtered image according to the second filtered image to obtain an intermediate image includes:

Subtracting the second filtered image from the first filtered image to obtain a difference image;

Obtaining the weighting factor of the difference image;

The intermediate image is obtained according to the difference image and the weighting factor of the difference image.
The method according to claim 5, wherein the weighting factor for acquiring the difference image includes:

Obtaining the sharpness of the difference image;

The weighting factor of the difference image is obtained according to the sharpness of the difference image.
The method according to any one of claims 1 to 6, wherein the superimposing the first filtered image and the intermediate image to obtain a target image further comprises:

Identify the noise of the target image;

Acquiring the noise ratio of the noise in the target image;

When the noise ratio of the target image is greater than the ratio threshold, the target image is used as the original image, and the step of acquiring the original image is performed.
An image processing device, characterized in that the device includes:

Acquisition module for acquiring original images;

A filtering processing module, configured to perform a first filtering process on the original image to obtain a first filtered image, and perform a second filtering process on the original image to obtain a second filtered image, wherein the clarity of the first filtered image Higher than the sharpness of the second filtered image;

A weakening processing module, configured to weaken the first filtered image according to the second filtered image to obtain an intermediate image;

The superimposition processing module is configured to superimpose the first filtered image and the intermediate image to obtain a target image.
A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, when the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.
A computer-readable storage medium on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are realized.