Image processing method and device, storage medium and electronic device

Abstract

The application discloses an image processing method and device, a storage medium and an electronic device. The image processing method comprises the following steps: acquiring at least one to-be-processed image of a display panel; detecting whether the to-be-processed image is an image acquired in a low-luminance environment; if yes, performing luminance processing on the to-be-processed image to improve the luminance of the to-be-processed image and generate a target image; determining a Mura area of the display panel based on the target image, and performing gray scale compensation on the Mura area. The present scheme can improve the accuracy of Demura data.

Description

Technical Field

[0001] This application relates to the field of image processing technology, specifically to an image processing method, apparatus, storage medium, and electronic device. Background Technology

[0002] With the development of display technology, liquid crystal displays (LCDs) have gradually replaced cathode ray tube (CRT) display devices due to their advantages such as being lightweight, thin, and having low radiation. LCDs are widely used in information terminals such as computers, smartphones, mobile phones, car navigation systems, and e-readers, becoming the most common display devices.

[0003] Due to manufacturing defects in LCD panels, uneven brightness is often produced, resulting in various types of Mura (Mura refers to uneven brightness in a display, causing various marks). For example, mixing 65-inch and 32-inch display panels often produces Mura in the splicing area. Currently, the Mura phenomenon is improved by preprocessing the images captured by the camera and then calculating Demura data using the Demura algorithm. The image preprocessing process is a very important part of Demura calculation.

[0004] However, while the camera sensor performs well in high light conditions, it struggles to capture accurate images in low light, resulting in inaccurate Demura data. Summary of the Invention

[0005] This application provides an image processing method, apparatus, storage medium, and electronic device that can improve the accuracy of Demura data.

[0006] In a first aspect, this application provides an image processing method, comprising:

[0007] Obtain at least one image to be processed from a display panel;

[0008] Detect whether the image to be processed was acquired in a low-brightness environment;

[0009] If so, then the image to be processed is subjected to brightness processing to increase the brightness of the image to be processed, thereby generating the target image;

[0010] The Mura region of the display panel is determined based on the target image, and grayscale compensation is performed on the Mura region.

[0011] In the image processing method provided in this application, when the number of images to be processed is greater than or equal to two, the step of performing brightness processing on the images to be processed to increase the brightness of the images to be processed and generating a target image includes:

[0012] The brightness value of each pixel in each of the multiple images to be processed is obtained;

[0013] The average brightness of each pixel is obtained based on the brightness value of each pixel.

[0014] Based on the average brightness, brightness processing is performed on one of the multiple images to be processed to generate the target image.

[0015] In the image processing method provided in this application, the step of performing brightness processing on one of the multiple images to be processed based on the average brightness value to generate a target image includes:

[0016] Based on the average brightness of each pixel, a first brightness adjustment is performed on one of the multiple images to be processed to generate a secondary image;

[0017] A second brightness adjustment is performed on the pixels whose brightness needs to be adjusted in the secondary image to generate the target image.

[0018] In the image processing method provided in this application, when the number of images to be processed is greater than or equal to two, the step of performing brightness processing on the images to be processed to increase the brightness of the images to be processed and generating a target image includes:

[0019] The multiple images to be processed are divided into multiple sub-images;

[0020] Obtain the brightness values ​​of multiple sub-images;

[0021] The target image is generated by performing brightness processing based on the brightness values ​​of the multiple sub-images.

[0022] In the image processing method provided in this application, the step of performing brightness processing based on the brightness values ​​of multiple sub-images to generate a target image includes:

[0023] The sub-images are grouped together, wherein the sub-images with the same part are grouped together;

[0024] The brightness difference between the brightness values ​​of multiple sub-images in each group and the corresponding preset brightness values ​​is obtained, and the sub-image with the smallest brightness difference in each group is taken as the target sub-image.

[0025] Multiple target sub-images are stitched together to generate a target image.

[0026] In the image processing method provided in this application, when the number of images to be processed is one, the step of performing brightness processing on the image to be processed to increase the brightness of the image to be processed and generating a target image includes:

[0027] The brightness of the image to be processed is increased using a pre-trained image brightening model to generate the target image.

[0028] In the image processing method provided in this application, after acquiring at least one image to be processed from a display panel and before detecting whether the image to be processed is an image acquired under low brightness conditions, the method further includes:

[0029] The image to be processed is subjected to noise reduction processing.

[0030] Secondly, this application provides an image processing apparatus, comprising:

[0031] The acquisition unit is used to acquire at least one image to be processed from a display panel;

[0032] The detection unit is used to detect whether the image to be processed is an image acquired in a low-brightness environment;

[0033] The processing unit is used to perform brightness processing on the image to be processed when the image to be processed is an image acquired in a low-brightness environment, so as to improve the brightness of the image to be processed and generate a target image;

[0034] The compensation unit is used to determine the Mura region of the display panel based on the target image and to perform grayscale compensation on the Mura region.

[0035] Thirdly, this application provides a storage medium storing a plurality of instructions adapted for loading by a processor to execute any of the image processing methods described above.

[0036] Fourthly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the image processing method described in any of the preceding claims.

[0037] In summary, the image processing method provided in this application can acquire at least one image of a display panel to be processed; detect whether the image to be processed is an image acquired in a low-brightness environment; if so, perform brightness processing on the image to be processed to increase its brightness and generate a target image; determine the Mura region of the display panel based on the target image, and perform grayscale compensation on the Mura region. This solution can improve the brightness of the image to be processed by performing brightness processing on the image to be processed acquired in a low-brightness environment, thereby improving the accuracy of the target image and thus improving the accuracy of the Demura data. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic flowchart of the image processing method provided in the embodiments of this application.

[0040] Figure 2 This is a schematic diagram of the structure of the image processing apparatus provided in the embodiments of this application.

[0041] Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0042] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0043] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment.

[0044] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0045] It should be noted that step designations such as 101 and 102 are used in this document for the purpose of more clearly and concisely describing the corresponding content, and do not constitute a substantial limitation on the order. In specific implementation, those skilled in the art may execute 102 first and then 101, etc., but these should all be within the protection scope of this application.

[0046] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0047] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0048] In the description of this application, it should be noted that the terms "upper," "lower," "left," "right," "inner," "outer," and "middle," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. In addition, terms such as "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0049] Due to manufacturing defects in LCD panels, uneven brightness is often produced, resulting in various types of Mura (Mura refers to uneven brightness in a display, causing various marks). For example, mixing 65-inch and 32-inch display panels often produces Mura in the splicing area. Currently, the Mura phenomenon is improved by preprocessing the images captured by the camera and then calculating Demura data using the Demura algorithm. The image preprocessing process is a very important part of Demura calculation.

[0050] However, while the camera sensor performs well in high light conditions, it struggles to capture accurate images in low light, resulting in inaccurate Demura data.

[0051] Based on this, embodiments of this application provide an image processing method, apparatus, storage medium, and electronic device. Specifically, the image processing apparatus can be integrated into an electronic device, which can be a server or a terminal, etc. The terminal can include mobile phones, wearable smart devices, tablet computers, laptops, and personal computers (PCs), etc. The server can be a single server or a server cluster composed of multiple servers, and can be a physical server or a virtual server.

[0052] The technical solutions shown in this application will be described in detail below through specific embodiments. It should be noted that the order of description of the following embodiments is not intended to limit the priority of the embodiments.

[0053] Please see Figure 1 , Figure 1 This is a schematic flowchart of the image processing method provided in an embodiment of this application. It should be noted that the image processing method can be specifically as follows:

[0054] 101. Obtain at least one image to be processed from a display panel.

[0055] The image to be processed can be an image captured by the camera after the electronic device starts the camera or camcorder, such as a frame captured by the camera when the user starts the camera application; or it can be an image taken by the user through the local camera.

[0056] The image to be processed can include static image files and dynamic image files. Static image files are image files containing only one frame, such as JPG format image files, PNG format image files, etc.; dynamic image files are image files containing multiple frames, such as video files, GIF format image files, etc.

[0057] 102. Detect whether the image to be processed was acquired in a low-brightness environment.

[0058] Understandably, the darker the ambient light, the higher the sensitivity of the camera when capturing images, and the longer the exposure time.

[0059] In this embodiment, the image to be processed is an image captured by an electronic device through a camera. Therefore, in some embodiments, the current sensitivity of the camera can be obtained, and it can be determined whether the current sensitivity of the camera is greater than a preset sensitivity. If the current sensitivity of the camera is greater than the preset sensitivity, it is considered that the image to be processed was captured in a low-light environment; otherwise, it is considered that the image to be processed was not captured in a low-light environment.

[0060] In another embodiment, the current exposure time of the camera can also be obtained, and it can be determined whether the current exposure time of the camera is greater than the preset exposure time. If the current exposure time of the camera is greater than the preset exposure time, it is considered that the image to be processed is an image obtained in a low-light environment; otherwise, it is considered that the image to be processed is not an image obtained in a low-light environment.

[0061] In some embodiments, the camera's sensitivity or exposure time when the image to be processed was captured can also be obtained from the attribute information of the image to be processed, and then the camera's sensitivity or exposure time in the attribute information can be used to determine whether the image to be processed was acquired in a low-light environment.

[0062] 103. If so, then brightness processing is performed on the image to be processed to increase its brightness and generate the target image.

[0063] In this embodiment of the application, when the number of images to be processed is one, the image to be processed can be directly input into a pre-trained image brightening model to improve the brightness of the image to be processed and generate the target image.

[0064] Understandably, due to the inconsistent performance of camera sensors, the brightness values ​​of each captured image may vary. Therefore, the more images to process, the more accurate the generated target image will be.

[0065] Therefore, in some embodiments, a target image with higher accuracy can be generated by obtaining the average brightness of multiple images to be processed, and then further processing one of the images to be processed based on the average brightness.

[0066] Specifically, the brightness value of each pixel in multiple images to be processed can be obtained separately; the average brightness value of each pixel can be obtained based on the brightness value of each pixel; and the brightness of one of the multiple images to be processed can be processed based on the average brightness value to generate the target image.

[0067] The step "perform brightness processing on one of the multiple images to be processed based on the average brightness value to generate the target image" may include:

[0068] Based on the average brightness of each pixel, a first brightness adjustment is performed on one of the multiple images to be processed to generate a secondary image;

[0069] Perform a second brightness adjustment on the pixels in the secondary image whose brightness needs to be adjusted, and generate the target image.

[0070] Understandably, the secondary image generated after the first brightness adjustment is more accurate than the image to be processed. The second brightness adjustment is then used to further improve image accuracy.

[0071] In some embodiments, the second brightness adjustment may specifically involve obtaining the brightness values ​​of all pixels in the secondary image, then comparing the brightness value of each pixel with a preset brightness value, thereby determining the pixel whose brightness needs to be adjusted based on the comparison result, and then increasing the brightness value of the pixel whose brightness needs to be adjusted to obtain the target image.

[0072] In another embodiment, when the number of images to be processed is greater than or equal to two, the step "perform brightness processing on the images to be processed to increase the brightness of the images to be processed and generate the target image" may include:

[0073] Multiple images to be processed are divided into multiple sub-images;

[0074] Obtain the brightness values ​​of multiple sub-images;

[0075] The target image is generated by performing brightness processing on the brightness values ​​of multiple sub-images.

[0076] It should be noted that dividing multiple images into segments means performing the same segmentation process on each image, with identical segmentation positions and sizes.

[0077] The step "perform brightness processing based on the brightness values ​​of multiple sub-images to generate the target image" may include:

[0078] Multiple sub-images are grouped together, with sub-images containing the same part forming a group;

[0079] The brightness difference between the brightness values ​​of multiple sub-images in each group and the corresponding preset brightness values ​​is obtained, and the sub-image with the smallest brightness difference in each group is taken as the target sub-image.

[0080] Multiple target sub-images are stitched together to generate the target image.

[0081] Understandably, due to the unstable performance of the camera sensor, the brightness values ​​of each captured image may vary. Therefore, the brightness values ​​of multiple sub-images within each group will also differ. To improve image accuracy, sub-images with brightness values ​​that are closest to a preset value can be selected as the target sub-image.

[0082] It should be noted that, in this embodiment of the application, in order to further improve image accuracy, after acquiring the image to be processed, noise reduction processing can be performed on the image to be processed before proceeding with subsequent processes. The specific process of this noise reduction processing can be performed using methods commonly used in the art, and will not be elaborated upon here.

[0083] 104. Determine the Mura region of the display panel based on the target image, and perform grayscale compensation on the Mura region.

[0084] It is understandable that the target image is generated by performing brightness processing on the image to be processed in a low-brightness environment to increase the brightness of the image to be processed. Therefore, its image accuracy is high. The state of the display panel can be reflected through this target image, thereby determining the Mura area of ​​the display surface. When performing grayscale compensation on the Mura area, the accuracy of the Demura data is high, thus improving the brightness uniformity of the display panel.

[0085] In summary, the image processing method provided in this application can acquire at least one image of a display panel to be processed; detect whether the image to be processed is acquired in a low-brightness environment; if so, perform brightness processing on the image to be processed to increase its brightness and generate a target image; determine the Mura region of the display panel based on the target image, and perform grayscale compensation on the Mura region. This solution can improve the brightness of the image to be processed by performing brightness processing on the image to be processed acquired in a low-brightness environment, thereby improving the accuracy of the target image and thus improving the accuracy of the Demura data.

[0086] To facilitate better implementation of the image processing method provided in the embodiments of this application, the embodiments of this application also provide an image processing apparatus. The meanings of the terms used are the same as in the image processing method described above, and specific implementation details can be found in the descriptions within the method embodiments.

[0087] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of this application. The image processing apparatus may include an acquisition unit 201, a detection unit 202, a processing unit 203, and a compensation unit 204.

[0088] The acquisition unit 201 is used to acquire at least one image to be processed from a display panel;

[0089] Detection unit 202 is used to detect whether the image to be processed is an image acquired in a low-brightness environment;

[0090] The processing unit 203 is used to perform brightness processing on the image to be processed when the image to be processed is an image acquired in a low-brightness environment, so as to improve the brightness of the image to be processed and generate a target image.

[0091] The compensation unit 204 is used to determine the Mura region of the display panel based on the target image and to perform grayscale compensation on the Mura region.

[0092] For specific implementation methods of each of the above units, please refer to the embodiments of the image processing method described above, which will not be repeated here.

[0093] In summary, the image processing apparatus provided in this application embodiment can acquire at least one image to be processed from a display panel by the acquisition unit 201; detect whether the image to be processed is acquired in a low-brightness environment by the detection unit 202; when the image to be processed is acquired in a low-brightness environment, the processing unit 203 performs brightness processing on the image to be processed to improve the brightness of the image to be processed and generate a target image; and the compensation unit 204 determines the Mura region of the display panel based on the target image and performs grayscale compensation on the Mura region. This solution can improve the brightness of the image to be processed by performing brightness processing on the image to be processed acquired in a low-brightness environment, thereby improving the accuracy of the target image and thus improving the accuracy of the Demura data.

[0094] This application also provides an electronic device that may integrate the image processing apparatus of this application, such as... Figure 3 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically:

[0095] The electronic device may include a radio frequency (RF) circuit 601, a memory 602 including one or more computer-readable storage media, an input unit 603, a display unit 604, a sensor 605, an audio circuit 606, a wireless Fidelity (WiFi) module 607, a processor 608 including one or more processing cores, and a power supply 609, etc. Those skilled in the art will understand that... Figure 3 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0096] in:

[0097] RF circuit 601 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and hands it over to one or more processors 608 for processing; additionally, it transmits uplink data to the base station. Typically, RF circuit 601 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, a low-noise amplifier (LNA), a duplexer, etc. Furthermore, RF circuit 601 can also communicate wirelessly with networks and other devices. Wireless communication can use any communication standard or protocol, including but not limited to GSM, GPRS, CDMA, WCDMA, LTE, email, and SMS.

[0098] The memory 602 can be used to store software programs and modules. The processor 608 executes various functional applications and information processing by running the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as audio data, telephone directory, etc.). In addition, the memory 602 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 602 may also include a memory controller to provide access to the memory 602 for the processor 608 and the input unit 603.

[0099] The input unit 603 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, in one embodiment, the input unit 603 may include a touch-sensitive surface and other input devices. The touch-sensitive surface, also known as a touch display or touchpad, can collect user touch operations on or near it (e.g., user operations using fingers, styluses, or any suitable object or accessory on or near the touch-sensitive surface), and drive corresponding connection devices according to a pre-set program. Optionally, the touch-sensitive surface may include a touch detection device and a touch controller. The touch detection device detects the user's touch orientation and the signal generated by the touch operation, transmitting the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 608, and can receive and execute commands from the processor 608. Furthermore, various types of touch-sensitive surfaces, such as resistive, capacitive, infrared, and surface acoustic wave, can be used. In addition to the touch-sensitive surface, the input unit 603 may also include other input devices. Specifically, other input devices may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0100] Display unit 604 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of electronic devices. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Display unit 604 may include a display panel, optionally configured as a liquid crystal display (LCD), organic light-emitting diode (OLED), or similar form. Furthermore, a touch-sensitive surface may cover the display panel. When the touch-sensitive surface detects a touch operation on or near it, it transmits the information to processor 608 to determine the type of touch event. Subsequently, processor 608 provides corresponding visual output on the display panel according to the type of touch event. Although in Figure 3 In this context, the touch-sensitive surface and the display panel are two separate components for implementing input and output functions. However, in some embodiments, the touch-sensitive surface and the display panel can be integrated to achieve both input and output functions.

[0101] The electronic device may also include at least one sensor 605, 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 can adjust the brightness of the display panel according to the ambient light level, and the proximity sensor can turn off the display panel and / or backlight when the electronic device is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. Other sensors that may be configured in the electronic device, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0102] Audio circuitry 606, a speaker, and a microphone provide an audio interface between the user and the electronic device. Audio circuitry 606 converts received audio data into electrical signals, transmits them to the speaker, and the speaker converts them into sound signals for output. Conversely, the microphone converts collected sound signals into electrical signals, which are then received by audio circuitry 606, converted back into audio data, and processed by processor 608. The processed data is then transmitted via RF circuitry 601 to, for example, another electronic device, or output to memory 602 for further processing. Audio circuitry 606 may also include an earphone jack to facilitate communication between external headphones and the electronic device.

[0103] WiFi is a short-range wireless transmission technology. Electronic devices using the WiFi module 607 can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 3 WiFi module 607 is shown, but it is understood that it is not a necessary component of an electronic device and can be omitted as needed without changing the nature of the invention.

[0104] The processor 608 is the control center of the electronic device. It connects various parts of the phone via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 602, and by calling data stored in the memory 602, thereby providing overall monitoring of the phone. Optionally, the processor 608 may include one or more processing cores; preferably, the processor 608 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 608.

[0105] The electronic device also includes a power supply 609 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 608 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 609 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0106] Although not shown, the electronic device may also include a camera, Bluetooth module, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 608 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 602 according to the following instructions, and the processor 608 runs the applications stored in the memory 602 to realize various functions, such as:

[0107] Obtain at least one image to be processed from a display panel;

[0108] Detect whether the image to be processed was acquired in a low-brightness environment;

[0109] If so, then brightness processing is performed on the image to be processed to increase its brightness and generate the target image;

[0110] The Mura region of the display panel is determined based on the target image, and grayscale compensation is performed on the Mura region.

[0111] In summary, the electronic device provided in this application acquires at least one image of a display panel to be processed; detects whether the image to be processed is acquired in a low-brightness environment; if so, it performs brightness processing on the image to be processed to increase its brightness and generate a target image; it determines the Mura region of the display panel based on the target image and performs grayscale compensation on the Mura region. This solution can improve the brightness of the image to be processed by performing brightness processing on the image to be processed acquired in a low-brightness environment, thereby improving the accuracy of the target image and thus improving the accuracy of the Demura data.

[0112] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed description of the image processing method above, which will not be repeated here.

[0113] It should be noted that, for the image processing method in the embodiments of this application, those skilled in the art will understand that all or part of the process of the image processing method in the embodiments of this application can be implemented by a computer program controlling the relevant hardware. The computer program can be stored in a computer-readable storage medium, such as the memory of a terminal, and executed by at least one processor in the terminal. During the execution process, it can include the process of the embodiments of the image processing method.

[0114] For the image processing apparatus of this application embodiment, its functional modules can be integrated into a single processing chip, or each module can exist physically separately, or two or more modules can be integrated into a single module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0115] Therefore, embodiments of this application provide a storage medium storing multiple instructions that can be loaded by a processor to execute the steps of any of the image processing methods provided in this application. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), etc.

[0116] The image processing method, apparatus, storage medium, and electronic device provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of this application. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An image processing method, characterized in that, include: Acquire at least one image to be processed from a display panel, wherein the image to be processed is a raw image captured by a camera for Demura detection; Obtain the current sensitivity or exposure time of the camera, and determine whether the sensitivity is greater than the preset sensitivity or the exposure time is greater than the preset exposure time; If so, then the image to be processed is subjected to brightness processing to increase the brightness of the image to be processed, thereby generating the target image; The Mura region of the display panel is determined based on the target image, and grayscale compensation is performed on the Mura region. Wherein, when the number of images to be processed is one, the step of performing brightness processing on the image to be processed to increase the brightness of the image to be processed and generating a target image includes: using a pre-trained image brightening model to increase the brightness of the image to be processed and generating a target image; When the number of images to be processed is greater than or equal to two, the step of performing brightness processing on the images to be processed to improve the brightness of the images to be processed and generate a target image includes: obtaining the average brightness of each pixel in the multiple images to be processed, and performing a first brightness adjustment on one of the multiple images to be processed based on the average brightness of each pixel to generate a secondary image; performing a second brightness adjustment on the pixels in the secondary image whose brightness needs to be adjusted to generate a target image; or, dividing the multiple images to be processed into multiple sub-images, wherein each image to be processed is subjected to the same cutting process, with the same cutting position and cutting size, obtaining the brightness values ​​of the multiple sub-images, grouping the multiple sub-images, wherein sub-images with the same part are grouped together, obtaining the brightness difference between the brightness values ​​of the multiple sub-images in each group and the corresponding preset brightness value, and taking the sub-image with the smallest brightness difference in each group as the target sub-image, and performing a stitching process on the multiple target sub-images to generate a target image.

2. The image processing method as described in claim 1, characterized in that, When the number of images to be processed is one, the step of performing brightness processing on the image to be processed to increase its brightness and generate a target image includes: The brightness of the image to be processed is increased using a pre-trained image brightening model to generate the target image.

3. The image processing method as described in claim 1 or 2, characterized in that, After acquiring at least one image to be processed from a display panel and before detecting whether the image to be processed was acquired in a low-brightness environment, the method further includes: The image to be processed is subjected to noise reduction processing.

4. An image processing apparatus, characterized in that, include: An acquisition unit is used to acquire at least one image to be processed from a display panel, wherein the image to be processed is a raw image captured by a camera for Demura detection; The detection unit is used to obtain the current sensitivity or exposure time of the camera, and determine whether the sensitivity is greater than the preset sensitivity or the exposure time is greater than the preset exposure time. The processing unit is configured to perform brightness processing on the image to be processed to increase the brightness of the image to be processed and generate a target image when the photosensitivity is greater than a preset photosensitivity or the exposure time is greater than a preset exposure time; wherein, when the number of images to be processed is one, the step of performing brightness processing on the image to be processed to increase the brightness of the image to be processed and generating a target image includes: using a pre-trained image brightening model to increase the brightness of the image to be processed and generating a target image; when the number of images to be processed is greater than or equal to two, the step of performing brightness processing on the images to be processed to increase the brightness of the image to be processed and generating a target image includes: obtaining the average brightness of each pixel in multiple images to be processed, and calculating the average brightness of each pixel based on its brightness... The average brightness is used to perform a first brightness adjustment on one of the multiple images to be processed, generating a secondary image; a second brightness adjustment is performed on the pixels in the secondary image whose brightness needs to be adjusted, generating a target image; or, the multiple images to be processed are divided into multiple sub-images, wherein each image to be processed is subjected to the same cutting process, with the same cutting position and cutting size, and the brightness values ​​of the multiple sub-images are obtained. The multiple sub-images are grouped, wherein sub-images with the same part are grouped together, and the brightness difference between the brightness values ​​of the multiple sub-images in each group and the corresponding preset brightness value is obtained. The sub-image with the smallest brightness difference in each group is taken as the target sub-image, and the multiple target sub-images are stitched together to generate the target image. The compensation unit is used to determine the Mura region of the display panel based on the target image and to perform grayscale compensation on the Mura region.

5. A storage medium, characterized in that, The storage medium stores a plurality of instructions, which are adapted for loading by a processor to execute the image processing method according to any one of claims 1-3.

6. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the image processing method as described in any one of claims 1-3.

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