JP2023180331A - Image processing method, device, electronic apparatus, and readable storage medium - Google Patents

Abstract

To provide an image processing method, a device, an electronic apparatus, and a readable storage medium.SOLUTION: A method according to the present invention includes: acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, the RGB camera and the at least one NIR camera being installed under a high transmission area of a display of an electronic apparatus; acquiring first information being flare information and/or ghost information on the basis of the first image signal and the second image signal; removing the first information from the first image signal to obtain a post-processing first image signal; and performing image fusion processing on the post-processing first image signal and the second image signal to obtain a fusion image.SELECTED DRAWING: Figure 1

Description

The present invention relates to the field of image processing technology, and particularly to an image processing method, device, electronic device, and readable storage medium.

Cameras on smartphones are mainly divided into a rear camera, which is installed on the opposite side of the display for mainly taking pictures, and a front camera, which is installed on the same side as the display, mainly for taking selfies. Since the front camera is installed on the same side as the display, its installation location must avoid the display, making it difficult to achieve a full-screen design where the entire front of the smartphone is the display. Currently, there are three types of front cameras: bezel type, where the front camera is installed on the outer bezel of the display, notch type, where the front camera is installed by making a hole in a part of the display, dot drop type, and punch hole type. Can be divided.

There are also examples of pop-up designs where the front camera is installed on the side of a smartphone and pops out when taking a picture, achieving full screen display. However, this design has issues with cost, thickness, reliability, and the time it takes to insert and remove the camera.

Therefore, in recent years, in order to solve the above-mentioned problems, under-screen cameras, that is, cameras that install the front camera under the display, have been further designed, and by increasing the transmittance of the display in the area where the camera is installed, The purpose of photographing is realized. However, as the transmittance of the display increases, there is a problem that the contrast of the display decreases and the uniformity with other parts of the display is impaired, so there is a limit to the transmittance of the display.

Because the transmittance of the display is limited, light is scattered by the display's constituent layers, causing flare and ghosting. Especially when there is a strong light source behind the subject, flare and ghosting are more noticeable. This causes the problem of image quality deterioration.

At least one embodiment of the present invention provides an image processing method, apparatus, electronic device, and readable storage medium, in which a conventional intelligent terminal uses an under-screen camera to capture images due to limited display transmittance. To solve the problem that when shooting images, flare and ghost occur due to light scattering in the display constituent layers, resulting in deterioration of the image quality of photographing.

In order to solve the above-mentioned technical problem, the present invention has been made as follows.

In a first aspect, embodiments of the invention include:
acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, wherein the RGB camera and the at least one NIR camera be located under the area,
obtaining first information that is flare information and/or ghost information based on the first image signal and the second image signal;
removing the first information from the first image signal to obtain a processed first image signal;
An image processing method is provided, which includes performing image fusion processing on the processed first image signal and the second image signal to obtain a fused image.

In a second aspect, embodiments of the invention include:
An acquisition module for acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, wherein the RGB camera and the at least one NIR camera an acquisition module installed under the high-transmission area of the display of the electronic device;
a first processing module for acquiring first information that is flare information and/or ghost information based on the first image signal and the second image signal;
a second processing module for removing the first information from the first image signal to obtain a processed first image signal;
An image processing device is provided, including a third processing module for performing image fusion processing on the processed first image signal and the second image signal to obtain a fused image.

In a third aspect, embodiments of the invention include:
comprising a processor, a memory, and a program or command stored in the memory and operable by the processor;
An electronic device is provided in which the steps of the image processing method described in the first aspect are realized when the program or command is executed by the processor.

In a fourth aspect, embodiments of the invention include:
Programs or commands are stored and
A readable storage medium is provided, in which the steps of the image processing method according to the first aspect are realized when the program or command is executed by a processor.

Compared with the prior art, the image processing method, apparatus, electronic device and readable storage medium provided by the embodiments of the present invention are such that the camera installed under the display of the electronic device combines an RGB camera and a NIR camera. In the case of By removing flare and/or ghost information from images, the effects of flare and ghosts are effectively eliminated and the image quality of shooting is improved.

1 is a schematic flowchart of an image processing method according to an embodiment of the present invention. 1 is a schematic configuration diagram of an underscreen camera device in which two cameras are arranged under a display of an electronic device according to an embodiment of the present invention. 3 is a schematic flowchart of an image processing method according to another embodiment of the present invention. FIG. 7 is a schematic configuration diagram of an underscreen camera device in which three cameras are arranged under the display of an electronic device according to another embodiment of the present invention. 7 is a schematic flowchart of an image processing method according to another embodiment of the present invention. 7 is a schematic flowchart of an image processing method according to yet another embodiment of the present invention. 1 is a schematic block diagram of an image processing device according to an embodiment of the present invention. 1 is a schematic configuration diagram of an electronic device according to an embodiment of the present invention.

The following clearly and completely describes the technical solutions according to the embodiments of the present application, together with the drawings according to the embodiments of the present application, and the described embodiments are part of the embodiments of the present application, Obviously not everything. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without any creative effort fall within the protection scope of the present application.

Terms such as "first" and "second" in the specification and claims of this application are used to distinguish between similar objects, and are not used to describe a particular order or sequential order. It's not a thing. The data used in this manner are interchangeable with each other in appropriate cases, such that the embodiments of the present application may be practiced in orders other than those illustrated or described herein, and the Objects that are distinguished by "," "second," etc. are usually of the same kind, and do not limit the number of objects; for example, it is understood that the first object may be one or more than one object. Should. In addition, "and/or" in the specification and claims represents at least one of the connected objects, and the symbol "/" generally means that the related objects before and after the "or". It represents being in a relationship.

In order to understand the technical solutions related to the present invention, the following describes related concepts according to the present invention.
Flare: When strong light passes through a lens, some of the light is reflected back to each of the lenses, and such internal reflections form an illusion, which is finally reflected in the photograph. This causes flare and causes the image to become blurred.
Ghost: This is caused by repeated reflections of strong light within the lens, and usually appears symmetrical to the light source.

As shown in FIG. 1, an embodiment of the present invention provides an image processing method, which may specifically include the following steps.

Step 101: Obtain a first image signal output from the RGB camera and a second image signal output from the at least one NIR camera, and the RGB camera and the at least one NIR camera It is installed below the transparent area.

In step 101, the RGB camera is also called a color camera, and the image taken by the RGB camera is a color image. R represents red, G represents green, and B represents blue. A variety of colors can be created by overlapping the three primary colors red, green, and blue in different ratios. The RGB camera is for receiving visible light.

A near-infrared (NIR) camera is for receiving near-infrared light. Near-infrared light is an electromagnetic wave that exists between visible light and mid-infrared light, and is invisible to the human eye. NIR cameras are applied to environments where near-infrared wavelength range is required, ie, environments with poor light irradiation conditions.

Step 102: Obtain first information, which is flare information and/or ghost information, based on the first image signal and the second image signal.

Specifically, by comparing the first image signal and the second image signal, difference information between the first image signal and the second image signal, that is, flare information and/or ghost information The first information is obtained.

From step 101, it can be seen that the embodiment of the present invention uses a combination of an RGB camera with wavelengths in the visible range and an NIR camera with wavelengths in the near-infrared range. Since the positions of the respective cameras are different, and the shapes of lenses, lens assembly precision, camera module assembly precision, etc. are also different for each camera, the states in which flare and ghosts occur are also different. Therefore, by performing subtraction on the image signals output from these cameras, a difference signal specific to flare and ghost can be obtained, and difference information between the first image signal and the second image signal can be obtained. Obtainable.

Step 103: Remove the first information from the first image signal to obtain a processed first image signal.

Step 104: Perform image fusion processing on the processed first image signal and second image signal to obtain a fused image.

In this example, image fusion processing is performed on the first image signal and the second image signal after processing to remove flare and/or ghost, thereby improving sensitivity in dark areas and reducing noise. At the same time, it is possible to synthesize and output a color image with improved luminance resolution, that is, a fused image, thereby achieving the purpose of improving image quality.

In one embodiment of the invention, step 102 described above may include the following steps.

Step 1021: Perform YUV conversion on the first image signal to obtain a Y signal and a UV signal, where Y represents luminance and UV represents color difference.

Specifically, the first image signal is converted from RGB to YUV and separated into a Y signal and a UV signal.

Step 1022: Based on the Y signal and the second image signal, obtain a difference signal indicating the difference between the first image signal and the second image signal.

Specifically, a difference signal is obtained by comparing the Y signal and the second image signal.

In one alternative embodiment, step 1022 described above may specifically include the following.

S1) Compare the Y signal and the second image signal output from each NIR camera to obtain N difference signals, where the value of N is equal to the number of NIR cameras.

This embodiment is applied when there is one or more NIR cameras.

Specifically, when there is one NIR camera, the Y signal and the second image signal output from the NIR camera are compared to obtain one difference signal.

When there are a plurality of NIR cameras, the Y signal and the second image signal output from each NIR camera are compared with each other to obtain a plurality of difference signals.

In another alternative embodiment, step 1022 may specifically include the following.

S11) When the number of NIR cameras is greater than 1, image fusion processing is performed on the second image signals output from each NIR camera, and a fused second image signal is obtained.

Each NIR camera has differences in angle of view, optical axis, and parallax, and in addition to detecting and correcting these differences, it is also possible to improve image resolution more effectively by using super-resolution processing. In this way, flare information and/or ghost information generated by each NIR camera is combined into the second image signal after fusion.

S12) Compare the Y signal and the second image signal after fusion to obtain a difference signal.

Step 1023: Obtain first information based on the difference signal.

In one embodiment of the invention, step 1023 described above may include the following.

S21) Calibrate the difference signal and obtain the calibrated difference signal.

S22) Contrast estimation and flare mask processing are performed on the calibrated difference signal to obtain first information.

In this embodiment, the RGB camera and the NIR camera have differences in angle of view, optical axis, and parallax, and in addition to detecting and correcting these differences, it is also necessary to perform contrast estimation and flare mask algorithm processing, etc. Thereby, different states of flare and/or ghost at each camera can be accurately detected, and only the first information, ie, flare information and/or ghost information, can be extracted.

In one embodiment of the invention, step 103 described above may include the following steps.

Step 1031: Remove the first information from the Y signal to obtain a processed Y signal.

Step 1032: Correct the UV signal based on the first information and the processed Y signal to obtain a corrected UV signal.

Since the UV signal output from the RGB camera is also affected by flare information and/or ghost information superimposed on the Y signal, the obtained first information, that is, flare information and/or ghost information, and the first It is necessary to correct the UV signal using the Y signal from which information has been removed, that is, the processed signal.

Correspondingly, step 104 described above may include the following steps.

Step 1041: Image fusion processing is performed on the processed Y signal, the corrected UV signal, and the second image signal to obtain a fused image.

Through the series of processes described above, flare and/or ghost can be separated from other images, and flare and/or ghost can be efficiently removed using this information. Flare and/or ghost caused by neon lights and LED lights, which are a big problem especially in night scenes, cannot be detected by a NIR camera and can therefore be effectively removed.

Hereinafter, specific implementation processes of the image processing method according to the present invention will be explained using three examples.

Example 1 In FIG. 2, an embodiment of an underscreen camera device is shown, in which two cameras are arranged below the display of an electronic device.

Camera 1 is an RGB camera, and camera 2 is an NIR camera. Camera 1 and camera 2 are installed under the high-transmission area of the display, and receive the light that has passed through the high-transmission area of the display and take an image.

In FIG. 3, a schematic flow diagram of the flare/ghost removal and image fusion process using output images from two underscreen cameras is shown.

a1) The output signal of the camera 1 is converted from RGB to YUV and then separated into a Y signal and a UV signal.

a2) Compare the output signal (near infrared light signal) of camera 2 and the Y signal of camera 1 to form a difference.

However, at this time, since there are differences between cameras 1 and 2 in terms of angle of view, optical axis, parallax, etc., it is necessary to detect and correct these differences, and also to set contrast estimation, flare mask algorithm processing, etc. , it is possible to accurately detect the difference between the flare occurrence state in camera 1 and the flare/ghost occurrence state in camera 2, and it is possible to extract only flare/ghost information.

a3) Using the obtained flare/ghost information, only the flare/ghost information is removed from the Y signal output from the camera 1.

a4) Correct the UV signal using the obtained flare/ghost information and the Y signal from which the flare/ghost information has been removed.

This step is performed because the UV signal output from the camera 1 is also affected by the flare/ghost information superimposed on the Y signal.

Through this series of processing, flare/ghost and other images can be separated, and flare/ghost can be efficiently removed using this information. Flare/ghosts caused by neon lights, LED lights, etc., which are a big problem when photographing night scenes, cannot be detected by a NIR camera, so the flare/ghosts caused by neon lights and LED lights can be efficiently eliminated through this series of processing.

a5) After flare/ghost removal, image fusion processing is performed using the Y signal and UV signal output from camera 1 and the near-infrared light signal output from camera 2, and then a color fused image is output.

By performing image fusion processing using the Y signal and UV signal output from camera 1 and the near-infrared light signal output from camera 2, sensitivity in dark areas is improved, noise is reduced, and brightness resolution It is possible to synthesize and output a color fused image with improved color fusion.

Example 2 FIG. 4 shows an embodiment of an underscreen camera device in which three cameras are arranged under the display of an electronic device.

Camera 1 is an RGB camera, and cameras 2 and 3 are NIR cameras. Camera 1, camera 2, and camera 3 are installed under the high-transmission area of the display, and receive the light that has passed through the high-transmission area of the display and take an image.

In example 1, there is a problem with the parallax detection accuracy because there are differences in resolution and optical characteristics between the RGB camera and the NIR camera. In this example, compared to example 1, two NIR cameras with high detection accuracy, especially in dark areas, are used, and accurate parallax information can be obtained between the NIR cameras, so the accuracy of the depth map is improved and face recognition is performed. Improve accuracy.

In FIG. 5, a schematic flow diagram of the flare/ghost removal and image fusion process using output images from three underscreen cameras is shown.

b1) The output signal of the camera 1 is converted from RGB to YUV and then separated into a Y signal and a UV signal.

b2) Image fusion of near-infrared light signals from cameras 2 and 3 to obtain a combined near-infrared light signal.

However, at this time, there are differences in the angle of view, optical axis, and parallax between cameras 2 and 3, so in addition to detecting and correcting these differences, super-resolution processing is used to improve the image resolution. Improve more effectively. Flare/ghost information generated by cameras 2 and 3 is combined with the near-infrared light signal thus combined.

b3) Compare the combined near-infrared light signal and the Y signal of camera 1 to form a difference.

At this time, there are differences in the angle of view, optical axis, and parallax between the near-infrared image and the image output from camera 1, so in addition to detecting and correcting these differences, contrast estimation, flare mask algorithm processing, etc. By going through these settings, it is possible to accurately detect the different states of flare/ghost in camera 1, camera 2, and camera 3, and it is possible to extract only the flare/ghost information.

b4) Using the obtained flare/ghost information, only the flare/ghost information is removed from the Y signal output from the camera 1.

b5) Correct the UV signal using the obtained flare/ghost information and the Y signal from which the flare/ghost information has been removed.

This step is performed because the UV signal output from the camera 1 is also affected by the flare/ghost information superimposed on the Y signal.

Through this series of processing, flare/ghost and other images can be separated, and flare/ghost can be efficiently removed using this information. Flare/ghosts caused by neon lights and LED lights, which are a big problem especially in night scenes, cannot be detected by a NIR camera, so they can be efficiently removed by a series of these processes.

b6) After flare/ghost removal, perform image fusion processing using the Y signal and UV signal output from camera 1 and the near-infrared light signals synthesized from cameras 2 and 3, and then create a color fused image. Output.

By performing image fusion processing using the Y signal and UV signal output from camera 1 and the near-infrared light signals synthesized from cameras 2 and 3, sensitivity in dark areas is improved and noise is reduced. At the same time, it is possible to synthesize and output a color fused image with improved luminance resolution.

Example 3 FIG. 6 shows a schematic flowchart of flare/ghost removal and image fusion processing using the output image from the underscreen camera device shown in FIG. 4.

c1) The output signal of the camera 1 is converted from RGB to YUV and then separated into a Y signal and a UV signal.

c2) Compare the output signal (near infrared light signal) of camera 2 and the Y signal of camera 1 to form a difference.

However, at this time, there are differences in the angle of view, optical axis, and parallax between the near-infrared image and the image output from camera 1, so in addition to detecting and correcting these differences, contrast estimation and flare mask algorithms are required. By going through settings such as processing, it is possible to accurately detect different states of flare/ghost between camera 1 and camera 2, and it is possible to extract only flare/ghost information.

c3) Compare the output signal (near infrared light signal) of camera 3 and the Y signal of camera 1 to form a difference.

However, at this time, there are differences in the angle of view, optical axis, and parallax between the near-infrared image and the image output from camera 1, so in addition to detecting and correcting these differences, contrast estimation and flare mask algorithms are required. By going through settings such as processing, it is possible to accurately detect different states of flare/ghost between cameras 1 and 3, and it is possible to extract only flare/ghost information.

c4) Using the obtained flare/ghost information, only the flare/ghost information is removed from the Y signal output from the camera 1.

c5) Correct the UV signal using the obtained flare/ghost information and the Y signal from which the flare/ghost information has been removed.

This step is performed because the UV signal output from the camera 1 is also affected by the flare/ghost information superimposed on the Y signal.

Through this series of processing, flare/ghost and other images can be separated, and flare/ghost can be efficiently removed using this information. Flare/ghosts caused by neon lights, LED lights, etc., which are a big problem when photographing night scenes, cannot be detected by a NIR camera, so the flare/ghosts caused by neon lights and LED lights can be efficiently eliminated through this series of processing.

c6) After flare/ghost removal, the Y signal and UV signal output from camera 1, the near-infrared light signal output from camera 2, and the near-infrared light signal output from camera 3 are used to create an image. After performing the fusion process, a color fused image is output.

By performing image fusion processing using the Y signal and UV signal output from camera 1, the near-infrared light signal output from camera 2, and the near-infrared light signal output from camera 3, It is possible to synthesize and output a color fused image with improved sensitivity in dark areas, reduced noise, and improved luminance resolution.

As shown in FIG. 7, the embodiment of the present invention further provides an image processing device, and the image processing device specifically includes:
an acquisition module 701 for acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, the RGB camera and the at least one NIR camera being electronically connected; an acquisition module 701 located under a high transmission area of a display of the device;
a first processing module 702 for obtaining first information, which is flare information and/or ghost information, based on the first image signal and the second image signal;
a second processing module 703 for removing first information from the first image signal to obtain a processed first image signal;
It can include a third processing module 704 for performing image fusion processing on the processed first image signal and second image signal to obtain a fused image.

Optionally, the first processing module 702 includes:
A first processing means for performing YUV conversion on the first image signal and obtaining a Y signal and a UV signal, where Y represents luminance and UV represents color difference. ,
a second processing means for obtaining a difference signal indicating a difference between the first image signal and the second image signal based on the Y signal and the second image signal;
and third processing means for obtaining the first information based on the difference signal.

Optionally, the second processing means specifically compares the Y signal and the second image signal output from each NIR camera to obtain N difference signals. Yes, and the value of N is equal to the number of NIR cameras.

Optionally, the second processing means specifically:
When the number of NIR cameras is greater than 1, image fusion processing is performed on the second image signal output from each NIR camera, and a fused second image signal is obtained;
This is for comparing the Y signal and the second image signal after fusion to obtain a difference signal.

Optionally, the third processing means specifically:
Perform calibration on the difference signal, obtain the difference signal after calibration,
This is to perform contrast estimation and flare mask processing on the calibrated difference signal to obtain first information.

Optionally, the second processing module 703
fourth processing means for removing the first information from the Y signal to obtain a processed Y signal;
A fifth processing means is included for correcting the UV signal based on the first information and the processed Y signal to obtain a corrected UV signal.

Optionally, the third processing module 704 includes:
It includes a sixth processing means for performing image fusion processing on the processed Y signal, the corrected UV signal, and the second image signal to obtain a fused image.

The advantages of the image processing apparatus according to the embodiment of the present invention are the same as the advantages of the embodiment of the image processing method, and will not be described again here.

As shown in FIG. 8, embodiments of the present invention further provide an electronic device 800. The electronic device 800 includes a processor 801, a memory 802, and a program or command stored in the memory 802 and operable by the processor 801, and when the program or command is executed by the processor 801, the above-described Each process in the embodiment of the image processing method described above can be implemented and similar technical effects can be achieved. To avoid duplication, they will not be restated here.

Note that the electronic devices in the embodiments of the present application include portable electronic devices and non-portable electronic devices.

Moreover, embodiments of the present invention further provide a readable storage medium. A program or a command is stored in the readable storage medium, and when the program or command is executed by a processor, each process in the embodiment of the image processing method described above is realized, and a similar technique is realized. effective effects can be achieved. To avoid duplication, they will not be restated here.

Although the embodiments of the present invention have been described above in conjunction with the drawings, the present invention is not limited to the above-described specific embodiments, and the above-described specific embodiments are only illustrative and are not limited. It's not something. Those skilled in the art can further make various forms under the guidance of the present invention without departing from the spirit of the present invention and the scope of protection in the claims, all of which belong to the protection of the present invention.

Claims (16)

acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, wherein the RGB camera and the at least one NIR camera be located under the area,
obtaining first information that is flare information and/or ghost information based on the first image signal and the second image signal;
removing the first information from the first image signal to obtain a processed first image signal;
An image processing method comprising: performing image fusion processing on the processed first image signal and the second image signal to obtain a fused image. Obtaining first information based on the first image signal and the second image signal includes:
performing YUV conversion on the first image signal to obtain a Y signal and a UV signal, where Y represents luminance and UV represents color difference;
obtaining a difference signal indicating a difference between the first image signal and the second image signal based on the Y signal and the second image signal;
The image processing method according to claim 1, further comprising: obtaining the first information based on the difference signal. Obtaining a difference signal based on the Y signal and the second image signal includes:
Comparing the Y signal and a second image signal output from each of the NIR cameras to obtain N difference signals,
The image processing method according to claim 2, characterized in that the value of N is equal to the number of said NIR cameras. Obtaining a difference signal based on the Y signal and the second image signal includes:
When the number of the NIR cameras is greater than 1, performing image fusion processing on the second image signal output from each of the NIR cameras to obtain a fused second image signal; and the Y signal and The image processing method according to claim 2, further comprising: comparing the fused second image signal to obtain a difference signal. Obtaining the first information based on the difference signal includes:
calibrating the difference signal and obtaining the calibrated difference signal;
The image processing according to any one of claims 2 to 4, further comprising performing contrast estimation and flare mask processing on the calibrated difference signal to obtain the first information. Method. Removing the first information from the first image signal to obtain a processed first image signal includes:
removing the first information from the Y signal to obtain a processed Y signal;
The image processing method according to claim 2, further comprising: correcting the UV signal based on the first information and the processed Y signal to obtain a corrected UV signal. Performing image fusion processing on the processed first image signal and the second image signal to obtain a fused image,
The image processing according to claim 6, further comprising performing image fusion processing on the processed Y signal, the corrected UV signal, and the second image signal to obtain a fused image. Method. An acquisition module for acquiring a first image signal output from an RGB camera and a second image signal output from at least one NIR camera, wherein the RGB camera and the at least one NIR camera an acquisition module installed under the high-transmission area of the display of the electronic device;
a first processing module for acquiring first information that is flare information and/or ghost information based on the first image signal and the second image signal;
a second processing module for removing the first information from the first image signal to obtain a processed first image signal;
An image processing device comprising: a third processing module for performing image fusion processing on the processed first image signal and the second image signal to obtain a fused image. The first processing module includes:
a first processing means for performing YUV conversion on the first image signal to obtain a Y signal and a UV signal, the first processing in which Y represents luminance and UV represents color difference; means,
a second processing means for obtaining a difference signal indicating a difference between the first image signal and the second image signal based on the Y signal and the second image signal;
The image processing apparatus according to claim 8, further comprising a third processing means for obtaining the first information based on the difference signal. The second processing means specifically compares the Y signal and a second image signal output from each of the NIR cameras to obtain N difference signals,
The image processing device according to claim 9, wherein the value of N is equal to the number of the NIR cameras. Specifically, the second processing means:
When the number of the NIR cameras is larger than 1, performing image fusion processing on the second image signal output from each of the NIR cameras to obtain a fused second image signal,
The image processing device according to claim 9, wherein the image processing device is for comparing the Y signal and the second image signal after fusion to obtain a difference signal. Specifically, the third processing means:
Calibrating the difference signal and obtaining the calibrated difference signal;
The image according to any one of claims 9 to 11, wherein the image is for performing contrast estimation and flare mask processing on the calibrated difference signal to obtain the first information. Processing equipment. The second processing module includes:
fourth processing means for removing the first information from the Y signal to obtain a processed Y signal;
10. A fifth processing means for correcting the UV signal based on the first information and the processed Y signal to obtain a corrected UV signal. image processing device. The third processing module includes:
Claim 13, further comprising: a sixth processing means for performing image fusion processing on the processed Y signal, the corrected UV signal, and the second image signal to obtain a fused image. The image processing device described in . comprising a processor, a memory, and a program or command stored in the memory and operable by the processor;
When the program or command is executed by the processor, the steps of the image processing method according to any one of claims 1 to 7 are realized.
An electronic device characterized by: Programs or commands are stored and
When the program or command is executed by a processor, the steps of the image processing method according to any one of claims 1 to 7 are realized.
A readable storage medium characterized by: