Image Processing Method, Apparatus, Electronic Device, and Storage Medium

Abstract

The present application discloses an image processing method, apparatus, electronic device and storage medium, belonging to the field of image technology. The method includes: obtaining a first original image and M second original images, where M is a positive integer; determining target noise data of an image sensor according to the M second original images; performing noise reduction processing on the first original image based on the target noise data to obtain a target image; wherein, when obtaining the first original image, the light transmittance of the light transmittance control layer is greater than 0; when obtaining the second original image, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original image.

Description

Technical Field

[0001] This application belongs to the technical field of image processing, and particularly relates to an image processing method, apparatus, electronic device, and storage medium. Background Art

[0002] Generally, in the scenario of taking images at night, an electronic device can perform noise reduction processing on a raw image output by an image sensor based on the pre-determined noise of the image sensor of the electronic device through an artificial intelligence (AI) noise reduction technology, so as to reduce the noise in the raw image. Thus, the electronic device can obtain a high-quality image based on the raw image after the noise reduction processing.

[0003] However, due to the possible influence of other factors (such as temperature change, etc.), the noise of the image sensor may change. Therefore, the effect of the electronic device performing noise reduction processing on the raw image through the AI noise reduction technology may be reduced, resulting in more noise still remaining in the raw image after the noise reduction processing.

[0004] As such, the quality of the images taken by the electronic device is poor. Summary of the Invention

[0005] The objective of the embodiments of this application is to provide an image processing method, apparatus, electronic device, and storage medium, which can improve the quality of the images taken by the electronic device.

[0006] In a first aspect, the embodiments of this application provide an image processing method, which is applied to an electronic device. The electronic device includes a light transmittance control layer disposed between a lens and an image sensor of the electronic device. The image processing method includes: obtaining a first raw image and M second raw images, where M is a positive integer; determining target noise data of the image sensor according to the M second raw images; performing noise reduction processing on the first raw image based on the target noise data to obtain a target raw image; wherein, when obtaining the first raw image, the light transmittance of the light transmittance control layer is greater than 0; when obtaining the second raw images, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first raw image is the same as the ISO sensitivity corresponding to the second raw images.

[0007] Second aspect, an embodiment of the present application provides an image processing apparatus, which is applied to an electronic device. The electronic device includes: a light transmittance control layer disposed between a lens and an image sensor of the electronic device; the image processing apparatus includes: an acquisition module, a determination module, and a processing module. The acquisition module is configured to acquire a first original image and M second original images, where M is a positive integer. The determination module is configured to determine target noise data of the image sensor according to the M second original images. The processing module is configured to perform noise reduction processing on the first original image based on the target noise data to obtain a target original image; wherein, when acquiring the first original image, the light transmittance of the light transmittance control layer is greater than 0; when acquiring the second original image, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original image.

[0008] Third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0009] Fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] Fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement the method described in the first aspect.

[0011] Sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the method described in the first aspect.

[0012] In the embodiments of the present application, the electronic device can acquire a first original image and M second original images to determine the target noise data of the image sensor, and perform noise reduction processing on the first original image according to the target noise data, so as to obtain a target image. In this solution, since the electronic device can acquire the target noise data in real time according to the M second original images, and perform noise reduction processing on the first original image according to the target noise data to obtain a target image, it is avoided that when the electronic device performs noise reduction processing on a captured image, due to the image sensor being unable to determine the accurate background noise in real time, the electronic device cannot accurately remove the noise, resulting in poor image quality of the image captured by the electronic device. Thus, the image quality of the image captured by the electronic device is improved. Description of the Drawings

[0013] Figure 1 It is a flowchart of an image processing method provided by an embodiment of the present application;

[0014] Figure 2 It is one of the schematic diagrams of an example of a light transmittance control layer provided by an embodiment of the present application;

[0015] Figure 3 It is one of the schematic diagrams of an example of an image processing method provided by an embodiment of the present application;

[0016] Figure 4 It is the second schematic diagram of an example of an image processing method provided by an embodiment of the present application;

[0017] Figure 5 It is one of the schematic diagrams of an example of an electronic device provided by an embodiment of the present application;

[0018] Figure 6 It is the second schematic diagram of an example of an electronic device provided by an embodiment of the present application;

[0019] Figure 7 It is the second schematic diagram of an example of a light transmittance control layer provided by an embodiment of the present application;

[0020] Figure 8 It is a schematic structural diagram of an image processing apparatus provided by an embodiment of the present application;

[0021] Figure 9 It is a schematic hardware structure diagram of an electronic device provided by an embodiment of the present application;

[0022] Figure 10 It is a schematic hardware structure diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0024] The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type and do not limit the number of objects. For example, the first object can be one or more. In addition, "and / or" in the description and claims means at least one of the connected objects, and the character " / ", generally indicates an "or" relationship between the associated objects before and after.

[0025] The terms related to the embodiments of this application will be described below.

[0026] 1. Image Sensor (Sensor)

[0027] The image sensor is the core of the camera and also the most critical technology in the camera. The Sensor can be divided into two types. One is the widely used Charge-coupled Device (CCD) element; the other is the Complementary Metal Oxide Semiconductor (CMOS) device. Compared with traditional cameras, traditional cameras use "film" as the carrier for recording information, while the "film" of digital cameras is their imaging photosensitive element. The photosensitive element is the non-replaceable "film" of digital cameras and is integrated with the camera.

[0028] Currently, the mainstream is the CMOS device. It, like the CCD, is a semiconductor that can record light changes in digital cameras. The working process of the CMOS is as follows: through a large number of photosensitive diodes (pixels), it senses the optical signal, then converts it into an electrical signal, and through an amplifier circuit and an analog / digital conversion circuit, forms a digital signal matrix (i.e., an image), which is then processed by an image signal processor and compressed for storage.

[0029] The CMOS camera module is the mainstream camera module used in current mobile phones and is mainly composed of a lens, a voice coil motor, an infrared filter, an image sensor (CMOS), a digital signal processor (DSP), and a flexible printed circuit (FPC).

[0030] The working process of a CCD camera module is as follows: The voice coil motor drives the lens to reach the accurately focused position. External light passes through the lens, is filtered by the infrared filter, and then irradiates onto the photosensitive diodes (pixels) of the image sensor. The photosensitive diodes convert the sensed optical signals into electrical signals, which form a digital signal matrix (i.e., an image) through an amplifier circuit and an analog-to-digital conversion circuit, and then are processed by a DSP and compressed for storage.

[0031] 2. Camera lens (lens)

[0032] The camera lens is the most important component in a camera because its quality directly affects the quality of the captured image. Lenses can be divided into two major categories: zoom lenses and fixed-focus lenses. A zoom lens has a variable focal length and a variable viewing angle, that is, a lens that can be zoomed in and out; a fixed-focus lens has a fixed focal length and only one focal length segment, or only one viewing angle.

[0033] 3. Fixed-Pattern Noise (FPN)

[0034] FPN usually exists in image sensors. This FPN is a type of fixed noise. When it is severe, it appears as fixed vertical stripes (Column FPN) or horizontal stripes (Row FPN). Sensor suppliers generally call them VFPN and HFPN. Generally speaking, FPN depends on factors such as the mismatch of column comparators, which leads to differences in the outputs of different columns, or the coupling effect between different rows, which causes horizontal stripes; as well as a poor power supply system, a mismatched clock source signal, and the module layer design may also cause FPN problems. This noise often varies in severity with the temperature of the entire electronic device and the sensor analog gain, and cannot be removed by noise reduction algorithms. When taking pictures in an extremely dark night environment, due to the weak image signal, FPN will bring a very bad visual experience.

[0035] 4. RAW image

[0036] A RAW image is the original data image obtained by converting the optical signals captured by a CMOS or CCD image sensor into digital signals.

[0037] Next, in combination with the accompanying drawings, the image processing method provided by the embodiments of the present application will be described in detail through specific embodiments and their application scenarios.

[0038] Currently, with the development of electronic devices, the shooting functions of cameras in electronic devices are becoming more and more diverse. However, the photo-taking effect of electronic devices in night scenes is poor. One of the reasons is that the size of the photosensitive diodes in electronic devices is too small, resulting in less light energy that can be collected by the photosensitive diodes in an environment with low light. When the backend (such as ISP) processes the optical signal transformation, a large amount of noise will be introduced to ensure that the brightness of the captured image meets the requirements of the user's human eyes.

[0039] In related technologies, to solve the above problems, noise reduction algorithms can be used to remove noise. These noise reduction algorithms can be divided into time-domain noise reduction and spatial-domain noise reduction. Typical methods of time-domain noise reduction are multi-frame noise reduction and wavelet noise reduction, aiming to remove the noise differences of single-pixel signals at different time periods. Typical methods of spatial-domain noise reduction are filter noise reduction, such as median filtering, Gaussian filtering, etc. However, these noise reduction means are often processed at the ISP backend, and the effect is not good. The recently popular AI noise reduction is performed at the front end and has a better effect than traditional time-domain and spatial-domain noise reduction. The premise of AI noise reduction is to accurately calculate the background noise. However, the background noise state of the image sensor changes with factors such as the camera startup time, ambient temperature, and mobile phone temperature, resulting in the inability of AI noise reduction to achieve the best effect. In addition, the fixed pattern noise of the image sensor cannot be removed by the noise reduction algorithm currently.

[0040] In the embodiments of the present application, an electronic device can obtain a first original image and M second original images to determine the target noise data of the image sensor, and perform noise reduction processing on the first original image according to the target noise data to obtain a target image. In this solution, since the electronic device can obtain the target noise data in real time according to the M second original images and perform noise reduction processing on the first original image according to the target noise data to obtain a target image, it is avoided that when the electronic device performs noise reduction processing on the captured image, due to the inability of the image sensor to determine the accurate background noise in real time, the electronic device cannot accurately remove the noise, resulting in poor image quality of the electronic device captured. Thus, the image quality of the electronic device captured is improved.

[0041] The embodiments of the present application provide an image processing method. Figure 1 The flowchart of an image method provided by the embodiments of the present application is shown. This method can be applied to an electronic device, and the electronic device includes: a light transmittance control layer disposed between the lens and the image sensor of the electronic device. As Figure 1 shown, the image processing method provided by the embodiments of the present application may include the following steps 201 to 203.

[0042] Step 201: The electronic device obtains a first original image and M second original images, where M is a positive integer.

[0043] In an embodiment of the present application, when obtaining the first original image, the light transmittance of the light transmittance control layer is greater than 0; when obtaining the second original image, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original image.

[0044] In an embodiment of the present application, the material of the above light transmittance control layer is an electrochromic material. In an embodiment of the present application, light passes through the light transmittance control layer by the lens and is projected onto the image sensor, so that the image sensor can convert the optical signal of the light into a digital signal of the original image, so that the electronic device can obtain the first original image and M second original images through the image sensor.

[0045] Optionally, in an embodiment of the present application, the above electrochromic material may be a redox reaction material or a dispersed liquid crystal material.

[0046] Optionally, in an embodiment of the present application, the above light transmittance control layer may be composed of at least one layer of electrochromic material.

[0047] Optionally, in an embodiment of the present application, the electronic device can change the light transmittance of the light transmittance control layer by changing the voltage across the light transmittance control layer.

[0048] Exemplarily, the electronic device can change the light transmittance of the electrochromic material by voltage. For example, when no voltage is applied across the electrochromic material, the light transmittance of the electrochromic material is 0, and when a second voltage (such as 2.8V) is applied across the electrochromic material, the light transmittance of the electrochromic material is 100%.

[0049] Optionally, in an embodiment of the present application, the electronic device can display the interface of the target application according to the click input of the user on the identifier (such as the application icon) of the target application, and turn on the camera of the electronic device. The electronic device can control the light transmittance of the light transmittance control layer to be the first light transmittance according to the first input of the user on the target control in the interface of the target application, so that the electronic device can obtain the first original image through the image sensor according to the click input of the user on the shooting control in the interface of the target application; furthermore, the electronic device can control the light transmittance of the light transmittance control layer to be the second light transmittance according to the second input of the user on the target control in the interface of the target application, so that the electronic device can obtain M second original images through the image sensor according to the click input of the user on the shooting control in the interface of the target application.

[0050] Optionally, in the embodiments of the present application, the above first input may be any one of the following: click input, long - press input, slide input, preset trajectory input; or a physical key combination (such as the power key and the volume key) input. Specifically, it can be determined according to actual usage requirements, and the embodiments of the present application do not make limitations. The above second input may be any one of the following: click input, long - press input, slide input, preset trajectory input; or a physical key combination (such as the power key and the volume key) input. Specifically, it can be determined according to actual usage requirements, and the embodiments of the present application do not make limitations.

[0051] Optionally, in the embodiments of the present application, the above first original image may be one original image or multiple original images.

[0052] It should be noted that the above first original image and the second original image are both images taken in the same environment.

[0053] Optionally, in the embodiments of the present application, the sizes of the above first original image and the second original image may be the same or different.

[0054] Optionally, in the embodiments of the present application, the above step 201 may be specifically implemented through the following step 201a and step 201b.

[0055] Step 201a: The electronic device controls the light transmittance of the light transmittance control layer to be the first light transmittance, and acquires the first original image through the image sensor.

[0056] In the embodiments of the present application, the electronic device may apply a preset voltage (such as 2.8V) to both ends of the light transmittance control layer, so that the light transmittance of the light transmittance control layer is 100%, and then the first original image is obtained through the first light transmittance.

[0057] Step 201b: The electronic device controls the light transmittance of the light transmittance control layer to be 0, and acquires M second original images through the image sensor.

[0058] In the embodiments of the present application, the electronic device may stop applying the preset voltage (such as 2.8V) to both ends of the light transmittance control layer, so that the light transmittance of the light transmittance control layer is 0, and then M second original images are obtained through the second light transmittance (i.e., the light transmittance is 0).

[0059] Exemplarily, taking the electrochromic material as a dispersed liquid crystal material as an example, as Figure 2As shown in (A) therein, when a voltage of 2.8V (i.e., the first voltage) is applied across the electronic device, the dispersed liquid crystal material 10 can adjust the small droplets in the liquid crystal sandwich according to the magnitude of the voltage, so that the matrix refractive index is relatively close. That is, when light is incident, the light can pass through and present a transparent state. At this time, the electronic device can collect a first original image through the current transmittance (i.e., the first transmittance), such as Figure 2 As shown in (B) therein, when no voltage is applied across the electronic device (i.e., the second voltage is 0), the small droplets in the liquid crystal sandwich of the dispersed liquid crystal material 10 are in a disordered state. When light is incident, its refractive index differs greatly from the matrix refractive index, and light scattering will occur when the light passes through, and the light transmission unit presents an opaque state (i.e., light cannot be incident on a plurality of photosensitive pixels). At this time, the electronic device can collect three second original images through the current transmittance (i.e., the second transmittance).

[0060] In the embodiments of the present application, the electronic device can apply a voltage across the light transmittance control layer, thereby changing the light transmittance of the light transmittance control layer to obtain a first original image and M second original images with different light transmittances, so that the electronic device can determine the true noise data of the image captured by the electronic device in the current environment through the first original image and the M second original images, improving the accuracy of the electronic device in processing the noise data in the image.

[0061] Optionally, in the embodiments of the present application, the "collecting the M second original images through the image sensor" in the above step 201 can be specifically implemented through the following step 201e.

[0062] Step 201e, when the target noise data includes fixed pattern noise data, the electronic device collects M second original images using a first exposure parameter.

[0063] In the embodiments of the present application, the above first exposure parameter is the exposure parameter when the image sensor collects the first original image.

[0064] In the embodiments of the present application, after the electronic device controls the transmittance of the light transmittance control layer to be the second transmittance, the electronic device can collect M second original images using the same exposure parameter as the first original image, so that the electronic device can compare the M second original images with the first original image to determine the fixed pattern noise data in the first original image.

[0065] Optionally, in the embodiments of the present application, the above fixed pattern noise data includes at least one of the following: row pattern noise data or column pattern noise data.

[0066] Optionally, in the embodiments of the present application, the above exposure parameters may include at least one of the following: shutter speed, aperture value (e.g., F2.8), sensitivity (e.g., ISO200), and exposure gain.

[0067] Optionally, in the embodiments of the present application, after the electronic device controls the transmittance of the light transmittance control layer to be the second transmittance, the electronic device may collect M second original images with the same gain (i.e., gain) as the first original image.

[0068] In the embodiments of the present application, the electronic device may collect M second original images with the same exposure parameters as the first original image, so that the electronic device can determine the fixed pattern noise data in the first original image according to the M second original images and the first original image. Furthermore, the electronic device can process the fixed pattern noise data, avoiding the situation that the electronic device cannot detect the fixed pattern noise and thus cannot process the fixed pattern noise, and improving the image quality of the images captured by the electronic device.

[0069] Step 202: The electronic device determines the target noise data of the image sensor according to the M second original images.

[0070] Optionally, in the embodiments of the present application, the above target noise data includes at least one of the following: read noise data and fixed pattern noise data.

[0071] Optionally, in the embodiments of the present application, the above step 202 may be specifically implemented by the following steps 202a to 202c.

[0072] Step 202a: The electronic device calculates K difference matrices according to the M second original images.

[0073] In the embodiments of the present application, the electronic device may process the pixel values of the M second original images to obtain K difference matrices.

[0074] Optionally, the above pixel values include at least one of the following: pixel brightness value, pixel saturation value, pixel quantity, and pixel color temperature value.

[0075] Specifically, the electronic device may obtain the pixel values of the M second original images and perform pairwise subtraction on the pixel values of the M second original images to obtain K difference matrices, where K = (M - 1)M / 2.

[0076] Exemplarily, taking M second original images as 3 for example, and taking a pixel point in one second original image as an example. Suppose the pixel values of the corresponding pixel points of the 3 second original images obtained by the electronic device are 64, 58, and 75 respectively. Then the electronic device can perform a difference operation on the pixel value of the first image and the pixel value of the second image, that is, 64 minus 58, to obtain the first difference matrix (6). Then the electronic device can perform a difference operation on the pixel value of the first image and the pixel value of the third image, that is, 64 minus 75, to obtain the second difference matrix (-11). Then the electronic device can perform a difference operation on the pixel value of the second image and the pixel value of the third image, that is, 58 minus 75, to obtain the third difference matrix (-17). Furthermore, the three difference matrices (i.e., the first difference matrix, the second difference matrix, and the third difference matrix) are saved.

[0077] Step 202b: The electronic device calculates the standard deviations of the K difference matrices respectively to obtain K standard deviations.

[0078] In the embodiments of the present application, the electronic device can calculate the standard deviations of the K difference matrices, so as to reflect the dispersion degree of the K difference matrices, that is, the noise data difference between the M second original images.

[0079] Step 202c: The electronic device calculates the average value of the K standard deviations to obtain the readout noise data.

[0080] Optionally, in the embodiments of the present application, the above readout noise data includes at least one of the following: additive noise data, multiplicative noise data, stationary noise data, or non-stationary noise data.

[0081] In the embodiments of the present application, the electronic device can obtain the real readout noise data in the current environment according to the M second original images. Thus, the electronic device can process the captured images according to the readout noise data, improving the accuracy of the electronic device in processing images.

[0082] Optionally, in the embodiments of the present application, the above step 202 can be specifically implemented by the following step 202d and step 202e.

[0083] Step 202d: The electronic device calculates an average pixel matrix according to the M second original images.

[0084] In the embodiments of the present application, the electronic device can calculate the average value of each pixel position in the M second original images to obtain the average pixel matrix of the M second original images.

[0085] Step 202e: The electronic device calculates the row standard deviation and column standard deviation of the average pixel matrix to obtain the target fixed pattern noise data.

[0086] In the embodiments of the present application, the electronic device can determine the vertical fixed pattern noise data and the horizontal column fixed pattern noise data in the M second original images by calculating the row standard deviation and the column standard deviation of the average pixel matrix.

[0087] In the embodiments of the present application, the electronic device can obtain the real target fixed pattern noise data in the current environment according to the M second original images, so that the electronic device can process the captured image according to the target fixed pattern noise data, improving the accuracy of the electronic device in processing images.

[0088] Step 203: The electronic device performs noise reduction processing on the first original image based on the target noise data to obtain a target image.

[0089] In the embodiments of the present application, after obtaining the target noise data, the electronic device can input the target noise data and the first original image into a preset model, and then obtain the target image.

[0090] It should be noted that the above target image is a digital signal image of the image collected by the camera by the user in the shooting preview interface.

[0091] Specifically, the electronic device can input the calculated target noise data and the first original image into the AI-NR algorithm model for processing to obtain the target image.

[0092] Optionally, in the embodiments of the present application, after the electronic device performs noise reduction processing on the first original image and the M second original images, the electronic device can input the noise-reduced first original image into an Image Signal Processor (ISP) to obtain the target image.

[0093] Optionally, in the embodiments of the present application, after obtaining the target image, the electronic device can store the obtained target image in a target application program (such as an album application program); or, the electronic device can display the target image on the shooting preview interface.

[0094] Optionally, in the embodiments of the present application, the above step 203 can be specifically implemented by the following steps 203a and 203b.

[0095] Step 203a: The electronic device corrects the initial noise calibration curve based on the readout noise data and the photon noise data to obtain an actual noise calibration curve.

[0096] It should be noted that the above photon noise data is the noise generated by the photosensitive element in the image sensor itself.

[0097] Specifically, photon noise is generated due to the change in the number of photons reaching the image sensor, resulting in a deviation between the actual situation and the theoretical situation.

[0098] In the embodiments of the present application, the electronic device can collect a color card image through a color card, and thus determine the initial read noise of the color card image according to the color card image. Then, the electronic device can obtain the total noise through a noise algorithm according to the initial read noise and the photon noise. The specific algorithm is as follows:

[0099] N 2 = P 2 + R 2 (Formula 1)

[0100] Where N is the total noise, P is the photon noise, and R is the initial read noise. Then, at each sensitivity (ISO value), the electronic device can obtain the initial noise calibration curve at each sensitivity according to the total noise and the signal value of the color card image. Then, the electronic device can correct the initial noise calibration curve through the read noise data and photon noise data obtained from M second original images to obtain the actual noise calibration curve. The calculation method of the initial read noise is the same as that in steps 202a - 202c, and the calculation method of the photon noise is to take the square root of the pixel value.

[0101] It can be understood that since the photon noise data is the noise generated by the photosensitive element in the image sensor itself and will not change due to the change of the shooting environment, the electronic device corrects the initial noise calibration curve by obtaining the actual read noise in different environments to obtain the actual noise calibration curve.

[0102] Exemplarily, as Figure 3 shown, the electronic device can shoot color card images at different sensitivities to obtain the initial read noise and photon noise at different sensitivities. Then, the electronic device can determine the initial noise calibration curve at different sensitivities according to the initial read noise and photon noise at different sensitivities. Among them, Figure 3 the horizontal axis in represents the average brightness of each color block, Figure 3 and the vertical axis in represents the square of the total noise.

[0103] Optionally, in the embodiments of the present application, the electronic device can obtain the slope and intercept of the initial noise calibration curve at different sensitivities according to the initial noise calibration curve at different sensitivities. The slope corresponds to the photon noise, and the intercept corresponds to the initial read noise.

[0104] Exemplarily, for the slopes at different sensitivities, as Figure 4 shown in (A) of, the electronic device can fit the slopes at different sensitivities to obtain a fitted slope curve. Among them, Figure 4In (A), the horizontal axis represents the sensitivity (ISO value), Figure 4 and the vertical axis in (A) represents the slope.

[0105] Exemplarily, for the intercepts at different sensitivities, as Figure 4 shown in (B), the electronic device can fit the intercepts at different sensitivities to obtain a fitted intercept curve, where Figure 4 the horizontal axis in (B) represents the sensitivity (ISO value), Figure 4 and the vertical axis in (B) represents the intercept.

[0106] It should be noted that since it is troublesome to record the initial noise calibration curve and it occupies a large amount of memory, the electronic device can obtain the slope and intercept at different ISO values according to the noise calibration curve at each ISO value, so as to characterize the initial noise calibration curve through the slope and intercept.

[0107] Step 203b: The electronic device performs noise reduction processing on the first original image based on the actual noise calibration curve.

[0108] In the embodiment of the present application, the read noise data obtained in step 203a actually corresponds to Figure 3 the actual intercept of the noise reduction curve at a certain ISO value in, so as to obtain a more accurate noise reduction curve.

[0109] In the embodiment of the present application, the electronic device can obtain the actual noise calibration curve according to the read noise data and the photon noise data, and then perform noise reduction processing on the first original image according to the actual noise calibration curve, that is, the electronic device can determine the actual noise calibration curve in real time according to the current environment, and then the electronic device performs noise reduction processing on the first original image according to the actual noise calibration curve. In this way, the quality of the images captured by the electronic device is improved.

[0110] Optionally, in the embodiment of the present application, the above step 203 can be specifically implemented by the following step 203d.

[0111] Step 203d: The electronic device performs noise reduction processing on the first original image based on the target fixed pattern noise data.

[0112] In the embodiment of the present application, the electronic device can subtract the fixed pattern noise data from the first original image according to the target fixed pattern noise, so as to obtain the first original image without fixed pattern noise.

[0113] It can be understood that since the first original image and the M second original images are all captured in the same environment, the fixed image noise data in the M second original images should be the same as the fixed image noise data on the first original image. Therefore, subtracting the target fixed image noise determined by the M second original images from the first original image can also remove the fixed image noise in the first original image.

[0114] In the embodiments of the present application, the electronic device can determine the target fixed image noise in real time according to the current environment, so that the electronic device performs noise reduction processing on the first original image according to the target fixed image noise. In this way, the quality of the images captured by the electronic device is improved.

[0115] The embodiments of the present application provide an image processing method. The electronic device can obtain a first original image and M second original images to determine the target noise data of the image sensor, and perform noise reduction processing on the first original image according to the target noise data, so as to obtain a target image. In this solution, since the electronic device can obtain the target noise data in real time according to the M second original images and perform noise reduction processing on the first original image according to the target noise data to obtain the target image, it is avoided that when the electronic device performs noise reduction processing on the captured image, due to the image sensor being unable to determine the accurate background noise in real time, the electronic device cannot accurately remove the noise, resulting in poor quality of the images captured by the electronic device. In this way, the quality of the images captured by the electronic device is improved.

[0116] Optionally, in the embodiments of the present application, before "acquiring M second original images through the image sensor" in step 201 above, the image processing method provided by the embodiments of the present application further includes the following step 301.

[0117] Step 301: When the target noise data includes readout noise data, the electronic device adjusts the first exposure parameter to the second exposure parameter.

[0118] In the embodiments of the present application, the above first exposure parameter is the exposure parameter when the image sensor captures the first original image, and the second exposure parameter is the exposure parameter when the image sensor captures the M second original images; wherein, the parameter value of the first exposure parameter is greater than the parameter value of the second exposure parameter.

[0119] In the embodiments of the present application, after the electronic device obtains the first original image, the electronic device can adjust the light transmittance of the electrochromic material to the second light transmittance, and use the second exposure parameter to capture the object M times to obtain M second original images.

[0120] It should be noted that the smaller the value of the above second exposure parameter, the more accurate the target noise data obtained based on the M second original images.

[0121] In the embodiments of the present application, the electronic device may capture M second original images with exposure parameters different from those of the first original image, so as to determine the noise floor data in the M second original images, and then process the first original image according to the noise floor data to obtain a target image with better noise reduction effect, improving the image quality captured by the electronic device.

[0122] Embodiments of the present application provide an electronic device. Figure 5 The following shows a schematic structural diagram of the electronic device provided by the embodiments of the present application. As Figure 5 shown, the electronic device provided by the embodiments of the present application includes: a light transmittance control layer 10 disposed between a lens 11 and an image sensor 12 of the electronic device.

[0123] Optionally, in the embodiments of the present application, the above-mentioned light transmittance control layer includes at least one light transmission unit, and each light transmission unit in the at least one light transmission unit is respectively arranged corresponding to a microlens layer; wherein, when a voltage is applied to the light transmittance control layer, the light transmittance of at least one light transmission unit in the light transmittance control layer changes, so that the light incident amount of the microlens layer changes.

[0124] Optionally, in the embodiments of the present application, the above-mentioned lens may be any one of the following: a telephoto lens, a short-focus lens, a fixed-focus lens, an ultra-wide-angle lens, a macro lens, etc.

[0125] Optionally, in the embodiments of the present application, combined Figure 5 , as Figure 6 shown, the above-mentioned electronic device further includes: a bracket 13 and a housing 14; wherein, the bracket 13 is disposed on both sides of the lens 11 for supporting the lens 11, the bracket 13 is connected to the housing 14, and the image sensor 12 is disposed on the housing 14.

[0126] Optionally, in the embodiments of the present application, the above-mentioned image sensor may be connected to the housing through a flexible printed circuit board.

[0127] Optionally, the number of the above-mentioned light transmittance control layers is at least two, and the at least two light transmittance control layers are stacked.

[0128] Exemplarily, as Figure 7 shown in (A) of

[0129] Again exemplarily, as Figure 7 shown in (B) of

[0130] Again exemplarily, as Figure 7As shown in (C) therein, the light transmittance control layer 10 can completely cover the microlens layer 16 in a column - covering or row - covering manner, so as to change the amount of incident light of the microlens layer.

[0131] Also, by way of example, as Figure 7 shown in (D) therein, the light transmittance control layer 10 can completely cover the microlens layer 16 in a block - covering manner, so as to change the amount of incident light of the microlens layer.

[0132] An embodiment of the present application provides an electronic device. The electronic device may include a lens, an image sensor, and a light transmittance control layer disposed between the lens and the image sensor. Thus, when a voltage is applied to the light transmittance control layer by the electronic device, the light transmittance of the light transmittance control layer can change, and then the light transmittance of the image sensor can be changed. Then, the electronic device can determine the noise data of the image sensor according to the changed light transmittance of the image sensor. In this solution, by relatively disposing the electrochromic material and the image sensor, the light transmittance obtained by the image sensor can be changed, that is, the electronic device can change the light transmittance obtained by the photosensitive pixels in any area of the image sensor. Thus, the noise data of the photosensitive pixels in the image sensor can be determined according to the changed light transmittance. Then, the electronic device can compensate the captured image according to the noise data, improving the image quality captured by the electronic device.

[0133] It should be noted that for the image processing method provided in the embodiment of the present application, the execution subject may be an image processing device. In the embodiment of the present application, taking the image processing device executing the image processing method as an example, the image processing device provided in the embodiment of the present application is described.

[0134] Figure 8 shows a possible structural schematic diagram of the image processing device involved in the embodiment of the present application. As Figure 8 shown, the image processing device 70 may include: an acquisition module 71, a determination module 72, and a processing module 73.

[0135] Among them, the acquisition module 71 is used to acquire a first original image and M second original images, where M is a positive integer. The determination module 72 is used to determine the target noise data of the image sensor according to the M second original images. The processing module 73 is used to perform noise reduction processing on the first original image based on the target noise data to obtain a target image; wherein, when acquiring the first original image, the light transmittance of the light transmittance control layer is greater than 0; when acquiring the second original image, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original image.

[0136] In a possible implementation, the above-mentioned acquisition module 71 is specifically configured to control the light transmittance of the light transmittance control layer to be a first light transmittance, and acquire a first original image through an image sensor; and control the light transmittance of the light transmittance control layer to be 0, and acquire M second original images through the image sensor.

[0137] In a possible implementation, the above-mentioned determination module 72 is specifically configured to calculate K difference matrices according to the M second original images; calculate the standard deviations of the K difference matrices respectively to obtain K standard deviations; and calculate the average value of the K standard deviations to obtain readout noise data.

[0138] In a possible implementation, the processing module 73 is specifically configured to correct an initial noise calibration curve based on the readout noise data and photon noise data to obtain an actual noise calibration curve; and perform noise reduction processing on the first original image based on the actual noise calibration curve.

[0139] In a possible implementation, the determination module 72 is specifically configured to calculate an average pixel matrix according to the M second original images; and calculate the row standard deviation and column standard deviation of the average pixel matrix to obtain target fixed pattern noise data.

[0140] In a possible implementation, the processing module 73 is specifically configured to perform noise reduction processing on the first original image based on the target fixed pattern noise data.

[0141] In a possible implementation, when the above-mentioned target noise data includes readout noise data; the processing module 73 is further configured to adjust the first exposure parameter to a second exposure parameter before the above-mentioned acquisition module 71 acquires M second original images through the image sensor, where the first exposure parameter is the exposure parameter when the image sensor acquires the first original image, and the second exposure parameter is the exposure parameter when the image sensor acquires M second original images; wherein, the parameter value of the first exposure parameter is greater than the parameter value of the second exposure parameter.

[0142] In a possible implementation, when the above-mentioned target noise data includes fixed pattern noise data; the above-mentioned acquisition module 71 is specifically configured to acquire M second original images by using the first exposure parameter, where the first exposure parameter is the exposure parameter when the image sensor acquires the first original image.

[0143] In a possible implementation, the material of the above light transmittance control layer is an electrochromic material. An embodiment of the present application provides an image processing device. Since the image processing device can obtain target noise data in real time according to M second original images, and perform noise reduction processing on the first original image according to the target noise data to obtain a target image, it is avoided that when the image processing device performs noise reduction processing on a captured image, since the image sensor cannot determine the accurate background noise in real time, the image processing device cannot accurately remove the noise, resulting in poor image quality of the image captured by the image processing device. Thus, the image quality of the image captured by the image processing device is improved.

[0144] The image processing device in the embodiment of the present application can be a device, or a component, an integrated circuit, or a chip in an electronic device. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a handheld computer, a vehicle-mounted electronic device, a Mobile Internet Device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. It can also be a server, a Network Attached Storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc. The embodiment of the present application does not make specific limitations.

[0145] The image processing device in the embodiment of the present application can be a device with an operating system. The operating system can be an Android operating system, an IOS operating system, or other possible operating systems. The embodiment of the present application does not make specific limitations.

[0146] The image processing device provided in the embodiment of the present application can implement Figures 1 to 8 each process implemented by the method embodiment. To avoid repetition, it will not be elaborated here.

[0147] Optionally, as Figure 9As shown in the figure, an embodiment of the present application further provides an electronic device 90, including a processor 91 and a memory 92. A program or instruction that can run on the processor 91 is stored on the memory 92. When the program or instruction is executed by the processor 91, each step of the above-described embodiment of the image processing method is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be elaborated here.

[0148] It should be noted that the electronic device in the embodiment of the present application includes the above-mentioned mobile electronic device and non-mobile electronic device.

[0149] Figure 10 It is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application.

[0150] The electronic device 100 includes, but is not limited to: a radio frequency unit 101, a network module 102, an audio output unit 103, an input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, and a processor 110 and other components.

[0151] Those skilled in the art can understand that the electronic device 100 may further include a power source (such as a battery) for supplying power to each component. The power source can be logically connected to the processor 110 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 10 The structure of the electronic device shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0152] Among them, the processor 110 is used to obtain a first original image and M second original images, where M is a positive integer; and determine the target noise data of the image sensor according to the M second original images; and perform noise reduction processing on the first original image based on the target noise data to obtain a target image; wherein, when obtaining the first original image, the light transmittance of the light transmittance control layer is greater than 0; when obtaining the second original image, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original image.

[0153] An embodiment of the present application provides an electronic device. Since the electronic device can obtain the target noise data in real time according to M second original images, and perform noise reduction processing on the first original image according to the target noise data to obtain a target image, it avoids that when the electronic device performs noise reduction processing on the captured image, due to the image sensor being unable to determine the accurate background noise in real time, resulting in the electronic device being unable to accurately remove the noise, and the image quality of the image captured by the electronic device is poor. Thus, the image quality of the image captured by the electronic device is improved.

[0154] Optionally, in the embodiments of the present application, the above-mentioned processor 110 is specifically configured to control the light transmittance of the electrochromic material to be a first light transmittance, and collect a first original image through the image sensor; and control the light transmittance of the electrochromic material to be 0, and collect M second original images through the image sensor.

[0155] Optionally, in the embodiments of the present application, the above-mentioned processor 110 is specifically configured to calculate K difference matrices according to the M second original images; calculate the standard deviations of the K difference matrices respectively to obtain K standard deviations; and calculate the average value of the K standard deviations to obtain the readout noise data.

[0156] Optionally, in the embodiments of the present application, the above-mentioned processor 110 is specifically configured to correct the initial noise calibration curve based on the readout noise data and the photon noise data to obtain an actual noise calibration curve; and perform noise reduction processing on the first original image based on the actual noise calibration curve.

[0157] Optionally, in the embodiments of the present application, the above-mentioned processor 110 is specifically configured to calculate an average pixel matrix according to the M second original images; and calculate the row standard deviation and column standard deviation of the average pixel matrix to obtain the target fixed pattern noise data.

[0158] Optionally, in the embodiments of the present application, the above-mentioned processor 110 is specifically configured to perform noise reduction processing on the first original image based on the target fixed pattern noise data.

[0159] Optionally, in the embodiments of the present application, when the above-mentioned target noise data includes readout noise data; the above-mentioned processor 110 is specifically configured to adjust the first exposure parameter to a second exposure parameter, where the first exposure parameter is the exposure parameter when the image sensor collects the first original image, and the second exposure parameter is the exposure parameter when the image sensor collects the M second original images; wherein, the parameter value of the first exposure parameter is greater than the parameter value of the second exposure parameter.

[0160] Optionally, in the embodiments of the present application, when the above-mentioned target noise data includes fixed pattern noise data; the above-mentioned processor 110 is specifically configured to collect M second original images using the first exposure parameter, where the first exposure parameter is the exposure parameter when the image sensor collects the first original image.

[0161] The electronic device provided by the embodiments of the present application can implement each process implemented by the above method embodiments and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0162] For the beneficial effects of various implementation manners in this embodiment, reference may specifically be made to the beneficial effects of the corresponding implementation manners in the above method embodiments. To avoid repetition, it will not be elaborated here.

[0163] It should be understood that in the embodiments of the present application, the input unit 104 may include a Graphics Processing Unit (GPU) 1041 and a microphone 1042. The graphics processor 1041 processes the image data of static pictures or videos obtained by an image capturing device (such as a camera) in a video capture mode or an image capture mode. The display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 107 includes at least one of a touch panel 1071 and other input devices 1072. The touch panel 1071 is also referred to as a touch screen. The touch panel 1071 may include two parts: a touch detection device and a touch controller. The other input devices 1072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, power on / off keys, etc.), a trackball, a mouse, and a joystick, which will not be elaborated here.

[0164] The memory 109 can be used to store software programs and various data. The memory 109 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area can store an operating system, application programs or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 109 can include volatile memory or non-volatile memory, or the memory 109 can include both volatile and non-volatile memory. Among them, the non-volatile memory can be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash memory. The volatile memory can be a Random Access Memory (RAM), a Static RAM (SRAM), a Dynamic RAM (DRAM), a Synchronous DRAM (SDRAM), a Double Data Rate SDRAM (DDR SDRAM), an Enhanced SDRAM (ESDRAM), a Synch link DRAM (SLDRAM), and a Direct Rambus RAM (DRRAM). The memory 109 in the embodiments of the present application includes but is not limited to these and any other suitable types of memory.

[0165] The processor 110 may include one or more processing units; optionally, the processor 110 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above modem processor may not be integrated into the processor 110 either.

[0166] The embodiments of the present application also provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above method embodiments and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0167] Among them, the processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disks, or optical discs, etc.

[0168] Another embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement each process of the above method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0169] It should be understood that the chip mentioned in the embodiments of the present application can also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0170] The embodiments of the present application provide a computer program product. The program product is stored in a storage medium and is executed by at least one processor to implement each process of the above image processing method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0171] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed. It may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described method may be executed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0172] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0173] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

Claims

1. An image processing method, applied to an electronic device, characterized in that The electronic device includes: a light transmittance control layer disposed between a lens and an image sensor of the electronic device; The method includes: Obtaining a first original image and M second original images, where M is a positive integer; Determining target noise data of the image sensor according to the M second original images; Performing noise reduction processing on the first original image based on the target noise data to obtain a target image; Wherein, when obtaining the first original image, the light transmittance of the light transmittance control layer is greater than 0; when obtaining the second original images, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original images; The determining the target noise data of the image sensor according to the M second original images includes: Calculating K difference matrices according to the M second original images; Respectively calculating the standard deviations of the K difference matrices to obtain K standard deviations; Calculating the average value of the K standard deviations to obtain readout noise data.

2. The method according to claim 1, wherein The obtaining the first original image and M second original images includes: Controlling the light transmittance of the light transmittance control layer to be a first light transmittance, and collecting the first original image through the image sensor; Controlling the light transmittance of the light transmittance control layer to be 0, and collecting the M second original images through the image sensor.

3. The method according to claim 1, wherein The performing noise reduction processing on the first original image based on the target noise data includes: Correcting an initial noise calibration curve based on the readout noise data and photon noise data to obtain an actual noise calibration curve; Performing noise reduction processing on the first original image based on the actual noise calibration curve.

4. The method according to claim 1, wherein The determining the target noise data of the image sensor according to the M second original images includes: Calculating an average pixel matrix according to the M second original images; Calculating the row standard deviation and column standard deviation of the average pixel matrix to obtain target fixed pattern noise data.

5. The method according to claim 4, wherein The performing noise reduction processing on the first original image based on the target noise data includes: Performing noise reduction processing on the first original image based on the target fixed pattern noise data.

6. The method according to claim 2, characterized in that, When the target noise data includes readout noise data; Before collecting the M second original images through the image sensor, the method further includes: Adjusting a first exposure parameter to a second exposure parameter, where the first exposure parameter is the exposure parameter when the image sensor collects the first original image, and the second exposure parameter is the exposure parameter when the image sensor collects the M second original images; Wherein, the parameter value of the first exposure parameter is greater than the parameter value of the second exposure parameter.

7. The method according to claim 2, wherein When the target noise data includes fixed pattern noise data; The collecting the M second original images through the image sensor includes: Collecting the M second original images using a first exposure parameter, where the first exposure parameter is the exposure parameter when the image sensor collects the first original image.

8. The method according to claim 1, wherein The material of the light transmittance control layer is an electrochromic material.

9. An image processing apparatus, applied to an electronic device, characterized in that The electronic device includes: a light transmittance control layer disposed between a lens and an image sensor of the electronic device; the image processing apparatus includes: an acquisition module, a determination module, and a processing module; The acquisition module is configured to acquire a first original image and M second original images, where M is a positive integer; The determination module is configured to determine target noise data of the image sensor according to the M second original images; The processing module is configured to perform noise reduction processing on the first original image based on the target noise data to obtain a target image; Wherein, when acquiring the first original image, the light transmittance of the light transmittance control layer is greater than 0; when acquiring the second original images, the light transmittance of the light transmittance control layer is 0; the ISO sensitivity corresponding to the first original image is the same as the ISO sensitivity corresponding to the second original images; The determination module is specifically configured to calculate K difference matrices according to the M second original images acquired by the acquisition module; calculate the standard deviations of the K difference matrices respectively to obtain K standard deviations; and calculate the average value of the K standard deviations to obtain readout noise data.

10. The device according to claim 9, characterized in that, The acquisition module is specifically configured to control the light transmittance of the light transmittance control layer to be a first light transmittance, and collect the first original image through the image sensor; and control the light transmittance of the light transmittance control layer to be 0, and collect the M second original images through the image sensor.

11. The device according to claim 9, characterized in that, The processing module is specifically configured to correct an initial noise calibration curve based on the readout noise data and photon noise data to obtain an actual noise calibration curve; and perform noise reduction processing on the first original image based on the actual noise calibration curve.

12. An electronic device, characterized in that, It includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the image processing method according to any one of claims 1 to 8 are implemented.

13. A readable storage medium, characterized in that, A program or instruction is stored on the readable storage medium. When the program or instruction is executed by a processor, the steps of the image processing method according to any one of claims 1 to 8 are implemented.

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