Method and device for determining noise reduction parameter, electronic equipment and storage medium

Abstract

The embodiment of the application relates to the technical field of image processing, and discloses a method and device for determining a noise reduction parameter, electronic equipment and a storage medium, the method comprising: determining a middle luminance of a normal image, the middle luminance being a median value of a plurality of luminances corresponding to pixel points included in the normal image; obtaining a preset noise reduction parameter set, the noise reduction parameter set comprising a first noise reduction parameter corresponding to a first pixel point with the middle luminance in the normal image; and determining a second noise reduction parameter of a second pixel point included in an overexposed image and an underexposed image according to the first noise reduction parameter and a first ratio, the first ratio being a ratio between a luminance of the second pixel point and a luminance of the first pixel point. The embodiment of the application can reduce the workload of noise reduction processing while ensuring the noise reduction effect on an HDR image.

Description

Technical Field

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

[0002] In pursuit of better image quality, camera devices can now achieve a wider dynamic range than ordinary digital imaging techniques through High Dynamic Range (HDR) imaging technology, resulting in HDR images with superior image quality.

[0003] In practice, it has been found that HDR images are usually obtained by fusing multiple frames of images with different exposures. Therefore, when performing noise reduction on HDR images, it is necessary to set different noise reduction parameters for multiple frames of images with different exposures. The process of setting noise reduction parameters is cumbersome, which increases the workload. Summary of the Invention

[0004] This application discloses a method, apparatus, electronic device, and storage medium for determining noise reduction parameters, which can reduce the workload of noise reduction processing while ensuring the noise reduction effect on HDR images.

[0005] The first aspect of this application discloses a method for determining noise reduction parameters, wherein a high dynamic range image is generated from a normal image, an overexposed image, and an underexposed image, wherein the exposure value corresponding to the overexposed image is greater than the exposure value corresponding to the normal image, and the exposure value corresponding to the underexposed image is less than the exposure value corresponding to the normal image, the method comprising:

[0006] Determine the median brightness of the normal image, wherein the median brightness is the median value of multiple brightness values ​​corresponding to the pixels included in the normal image;

[0007] Obtain a preset set of noise reduction parameters, the set of noise reduction parameters including the first noise reduction parameter corresponding to the first pixel point in the normal image whose brightness is the intermediate brightness;

[0008] Based on the first noise reduction parameter and the first ratio, a second noise reduction parameter is determined for the second pixel points included in the overexposed image and the underexposed image, wherein the first ratio is the ratio between the brightness of the second pixel point and the brightness of the first pixel point.

[0009] As an optional implementation, in the first aspect of the embodiments of this application, the noise reduction parameter set further includes a third noise reduction parameter corresponding to a third pixel point with a brightness of a first brightness in the normal image, and a fourth noise reduction parameter corresponding to a fourth pixel point with a brightness of a second brightness in the normal image, wherein the first brightness is higher than the intermediate brightness, and the second brightness is lower than the intermediate brightness;

[0010] The step of determining the second noise reduction parameter for the second pixels included in the overexposed image and the underexposed image based on the first noise reduction parameter and the first ratio includes:

[0011] Based on the first noise reduction parameter and the first ratio, a second noise reduction parameter is determined for the second pixel point in the overexposed image and the underexposed image whose brightness is between the first brightness and the second brightness.

[0012] The fifth noise reduction parameter is determined based on the third noise reduction parameter for the fifth pixel point in the overexposed image and the underexposed image whose brightness is greater than the first brightness.

[0013] The sixth noise reduction parameter is determined based on the fourth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image.

[0014] As an optional implementation, in a first aspect of the embodiments of this application, determining the fifth noise reduction parameter of the fifth pixel point whose brightness is greater than the first brightness in the overexposed image and the underexposed image based on the third noise reduction parameter includes:

[0015] Based on the third noise reduction parameter and the second ratio, a fifth noise reduction parameter is determined for the fifth pixel in the overexposed image and the underexposed image whose brightness is greater than the first brightness. The second ratio is the ratio between the brightness of the fifth pixel and the brightness of the third pixel.

[0016] And, determining the sixth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image based on the fourth noise reduction parameter includes:

[0017] Based on the fourth noise reduction parameter and the third ratio, a sixth noise reduction parameter is determined for the sixth pixel in the overexposed image and the underexposed image whose brightness is less than the second brightness. The third ratio is the ratio between the brightness of the sixth pixel and the brightness of the fourth pixel.

[0018] As an optional implementation, in a first aspect of the embodiments of this application, determining the fifth noise reduction parameter of the fifth pixel point whose brightness is greater than the first brightness in the overexposed image and the underexposed image based on the third noise reduction parameter includes:

[0019] The fifth noise reduction parameter is determined based on the third noise reduction parameter for the fifth pixel in the underexposed image whose brightness is greater than the first brightness.

[0020] The noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness is set as the target noise reduction parameter, and the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0021] As an optional implementation, in a first aspect of this application, determining the sixth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image based on the fourth noise reduction parameter includes:

[0022] The sixth noise reduction parameter is determined based on the fourth noise reduction parameter for the sixth pixel in the overexposed image whose brightness is less than the second brightness.

[0023] The noise reduction parameter of the sixth pixel in the underexposed image whose brightness is less than the second brightness is set as the target noise reduction parameter, and the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0024] As an optional implementation, in the first aspect of the embodiments of this application, after obtaining the preset noise reduction parameter set, the method further includes:

[0025] Based on the first noise reduction parameter and the fourth ratio, the seventh noise reduction parameter of the seventh pixel in the normal image, excluding the first pixel, is determined, wherein the fourth ratio is the ratio between the brightness of the seventh pixel and the brightness of the first pixel.

[0026] As an optional implementation, in a first aspect of this application, after determining the second noise reduction parameters of the second pixels included in the overexposed image and the underexposed image based on the first noise reduction parameter and the first ratio, the method further includes:

[0027] The normal image, overexposed image, and underexposed image are respectively subjected to noise reduction processing to obtain the target normal image, target overexposed image, and target underexposed image;

[0028] A high dynamic range image of the target is generated based on the normal image of the target, the overexposed image of the target, and the underexposed image of the target.

[0029] A second aspect of this application discloses a device for determining noise reduction parameters. A high dynamic range image is generated from a normal image, an overexposed image, and an underexposed image. The overexposed image has an exposure value greater than the normal image's exposure value, and the underexposed image has an exposure value less than the normal image's exposure value. The device includes:

[0030] The first determining unit is used to determine the median brightness of the normal image, wherein the median brightness is the median value of multiple brightness values ​​corresponding to the pixels included in the normal image.

[0031] The acquisition unit is used to acquire a preset set of noise reduction parameters, the set of noise reduction parameters including a first noise reduction parameter corresponding to a first pixel in the normal image whose brightness is the intermediate brightness;

[0032] The second determining unit is configured to determine, based on the first noise reduction parameter and the first ratio, a second noise reduction parameter for the second pixel points included in the overexposed image and the underexposed image, wherein the first ratio is the ratio between the brightness of the second pixel point and the brightness of the first pixel point.

[0033] The third aspect of this application discloses an electronic device, including:

[0034] Memory containing executable program code;

[0035] A processor coupled to the memory;

[0036] The processor calls the executable program code stored in the memory to execute the method for determining noise reduction parameters disclosed in the first aspect of the embodiments of this application.

[0037] A fourth aspect of this application discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the method for determining noise reduction parameters disclosed in the first aspect of this application.

[0038] The fifth aspect of this application discloses a computer program product that, when run on a computer, causes the computer to perform some or all of the steps of any method of the first aspect of this application.

[0039] The sixth aspect of this application discloses an application publishing platform for publishing computer program products, wherein when the computer program products are run on a computer, the computer performs some or all of the steps of any one of the methods of the first aspect of this application.

[0040] Compared with related technologies, the embodiments of this application have the following beneficial effects:

[0041] In this embodiment, the median brightness of the normal image used to synthesize the high dynamic range image can be determined first. This median brightness is the median value of multiple brightness values ​​corresponding to the pixels in the normal image. Then, a preset set of noise reduction parameters can be obtained. This set of noise reduction parameters can include a first noise reduction parameter corresponding to a first pixel in the normal image with a median brightness. Then, based on the first noise reduction parameter and a second ratio, a second noise reduction parameter for the second pixels in the overexposed and underexposed images used to synthesize the high dynamic range image can be determined. The first ratio is the ratio of the brightness of the second pixel to the brightness of the first pixel. Therefore, implementing this embodiment only requires obtaining the first noise reduction parameter of the median brightness of the normal image. The second noise reduction parameter for each second pixel in the overexposed and underexposed images can be automatically determined by brightness interpolation, thus reducing the workload of determining the noise reduction parameters. Furthermore, since the second noise reduction parameter for each second pixel in the overexposed and underexposed images is determined by brightness interpolation, the second noise reduction parameter is more closely matched to the second pixel, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating a method for determining noise reduction parameters disclosed in an embodiment of this application;

[0044] Figure 2 This is a flowchart illustrating another method for determining noise reduction parameters disclosed in an embodiment of this application;

[0045] Figure 3 This is a schematic diagram of brightness distribution disclosed in an embodiment of this application;

[0046] Figure 4 This is a flowchart illustrating another method for determining noise reduction parameters disclosed in the embodiments of this application;

[0047] Figure 5 This is a schematic diagram of the structure of a noise reduction parameter determination device disclosed in an embodiment of this application;

[0048] Figure 6 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0050] It should be noted that the terms "first," "second," "third," and "fourth," etc., used in the specification and claims of this application are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, in the embodiments of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0051] This application discloses a method, apparatus, electronic device, and storage medium for determining noise reduction parameters, which can reduce the workload of noise reduction processing while ensuring the noise reduction effect on HDR images.

[0052] The technical solution of this application will be described in detail below with reference to specific embodiments.

[0053] Optionally, the method for determining noise reduction parameters disclosed in this application can be applied to various electronic devices with image processing capabilities, such as mobile phones, tablets, cameras, or smartwatches, and is not limited thereto. Optionally, when the electronic device has HDR shooting function enabled, after the electronic device has acquired multiple frames of images to be synthesized at different exposures for the same scene, the noise reduction parameters corresponding to each frame of the images to be synthesized can be determined by this method.

[0054] To more clearly illustrate the method, apparatus, electronic device, and storage medium for determining noise reduction parameters disclosed in this application, we will first introduce how to set the noise reduction parameters for HDR images in HDR images, image noise reduction techniques, and related technologies.

[0055] HDR images, generated using High Dynamic Range (HDR) imaging technology, have a wider dynamic range than ordinary digital images, resulting in superior image quality. The camera device can capture images of the same target scene at different exposure levels, obtaining images of the target scene at varying exposures. These images are then fused to create an HDR image of the target scene.

[0056] Image denoising technology is a technique that removes noise from an image using a preset denoising algorithm to improve image quality. Denoising algorithms can include Gaussian filtering, mean filtering, etc., and are not limited here. The degree of denoising, i.e., the extent to which noise is removed, is related to the set denoising parameters; that is, different denoising effects can be achieved by setting different parameters.

[0057] In related technologies, it is typically necessary to first perform noise reduction processing on target scene images at different exposures, and then generate a noise-reduced HDR image based on multiple noise-reduced target scene images. However, in practice, it has been found that in order to ensure optimal noise reduction for target scene images at different exposures, developers usually need to manually set the corresponding noise reduction parameters for target scene images at different exposures, thus increasing the workload for developers. On the other hand, if the same noise reduction parameters are used for target scene images at different exposures in order to reduce the workload for developers, it will result in poor subsequent noise reduction.

[0058] The method for determining noise reduction parameters disclosed in this application can first determine the median brightness of the normal image used to synthesize the high dynamic range image. This median brightness is the median value of multiple brightness values ​​corresponding to the pixels in the normal image. Then, a preset set of noise reduction parameters can be obtained. This set of noise reduction parameters can include the first noise reduction parameter corresponding to the first pixel in the normal image with the median brightness. Then, based on the first noise reduction parameter and the second ratio, the second noise reduction parameter of the second pixel in the overexposed and underexposed images used to synthesize the high dynamic range image can be determined. The first ratio is the ratio of the brightness of the second pixel to the brightness of the first pixel. As can be seen, by implementing the embodiments of this application, it is only necessary to obtain the first noise reduction parameter of the intermediate brightness of the normal image. That is, the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images can be automatically determined by brightness interpolation, thereby reducing the workload of determining the noise reduction parameter. In addition, since the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images is determined based on the brightness interpolation of each second pixel point, the second noise reduction parameter is more closely matched to the second pixel point, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images.

[0059] Based on this, the method for determining the noise reduction parameters disclosed in the embodiments of this application will be described below.

[0060] Please see Figure 1 , Figure 1This is a flowchart illustrating a method for determining noise reduction parameters disclosed in an embodiment of this application. Optionally, this method can be applied to various electronic devices with image processing capabilities, such as mobile phones, tablets, cameras, or smartwatches, etc., and is not limited thereto. Optionally, the method may include the following steps:

[0061] 102. Determine the median brightness of a normal image. The median brightness is the median value of the brightness values ​​of the pixels in a normal image.

[0062] Optionally, the high dynamic range image can be generated from three frames: a normal image, an overexposed image, and an underexposed image. The overexposed image can have a higher exposure value than the normal image, and the underexposed image can have a lower exposure value than the normal image. Alternatively, the normal image, overexposed image, and underexposed image can be images captured separately for the same target scene.

[0063] In some alternative embodiments, to improve the image quality of the high dynamic range image, the high dynamic range image may also be generated from three or more frames, for example, from four or five frames, without limitation. The exposure levels of the three or more frames are different. For ease of explanation, this application uses the example of a high dynamic range image being generated from three frames: a normal image, an overexposed image, and an underexposed image, and this should not be construed as limiting the scope of this application.

[0064] Optionally, the electronic device may also have a shooting capability, and the normal image, overexposed image, and underexposed image may be captured by the electronic device. In another embodiment, the normal image, overexposed image, and underexposed image may be acquired by the electronic device from other devices or the Internet, which is not limited thereto.

[0065] Furthermore, the electronic device can acquire multiple brightness values ​​corresponding to the pixels in the normal image, and then determine the median value of the multiple brightness values ​​as the median brightness of the normal image. The median value is obtained by arranging the multiple brightness values ​​from smallest to largest or largest to smallest, and the brightness value in the middle of the arrangement is the median value.

[0066] 104. Obtain the preset noise reduction parameter set, which includes the first noise reduction parameter corresponding to the first pixel point with intermediate brightness in the normal image.

[0067] In this embodiment of the application, after determining the intermediate brightness of a normal image, the electronic device can obtain a set of noise reduction parameters including a first noise reduction parameter, wherein the first noise reduction parameter is the first noise reduction parameter corresponding to the first pixel point with intermediate brightness in the normal image.

[0068] Optionally, the preset noise reduction parameter set can be set by developers based on extensive development experience, or it can be set by electronic devices based on users' noise reduction needs; there are no restrictions here.

[0069] 106. Based on the first noise reduction parameter and the first ratio, determine the second noise reduction parameter for the second pixel points included in the overexposed image and the underexposed image, wherein the first ratio is the ratio between the brightness of the second pixel point and the brightness of the first pixel point.

[0070] In this embodiment, the difference between the second pixel and the first pixel in the overexposed and underexposed images includes the difference in brightness. Since the noise reduction effect is different after performing noise reduction processing on pixels with different brightness using the same noise reduction parameters, the brightness of a pixel is one of the factors determining the noise reduction effect. Optionally, the electronic device can determine the second noise reduction parameters of the second pixel in the overexposed and underexposed images based on the first noise reduction parameters corresponding to the first pixel and a first ratio, wherein the first ratio is the ratio between the brightness of the second pixel and the brightness of the first pixel.

[0071] Optionally, the electronic device may calculate a first product of a first noise reduction parameter and a first ratio as a second noise reduction parameter corresponding to the second pixel.

[0072] For example, if the brightness of the first pixel is 100, the corresponding first noise reduction parameter is 10; if the brightness of the second pixel is 200, then the corresponding second noise reduction parameter for the second pixel is 200.

[0073] It should be noted that the second pixel can be any of the pixels included in both overexposed and underexposed images, and is not limited here.

[0074] By implementing the methods disclosed in the above embodiments, the intermediate brightness of the normal image used to synthesize the high dynamic range image can be determined first. The intermediate brightness is the median value of multiple brightness values ​​corresponding to the pixels included in the normal image. Then, a preset set of noise reduction parameters can be obtained. The set of noise reduction parameters can at least include the first noise reduction parameter corresponding to the first pixel in the normal image with the intermediate brightness. Then, based on the first noise reduction parameter and the second ratio, the second noise reduction parameter of the second pixel included in the overexposed and underexposed images used to synthesize the high dynamic range image can be determined. The first ratio is the ratio of the brightness of the second pixel to the brightness of the first pixel. As can be seen, by implementing the embodiments of this application, it is only necessary to obtain the first noise reduction parameter of the intermediate brightness of the normal image. That is, the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images can be automatically determined by brightness interpolation, thereby reducing the workload of determining the noise reduction parameter. In addition, since the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images is determined based on the brightness interpolation of each second pixel point, the second noise reduction parameter is more closely matched to the second pixel point, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images.

[0075] Please see Figure 2 , Figure 2 This is a flowchart illustrating another method for determining noise reduction parameters disclosed in an embodiment of this application. Optionally, this method can be applied to various electronic devices with image processing capabilities, such as mobile phones, tablets, cameras, or smartwatches, etc., and is not limited thereto. Optionally, the method may include the following steps:

[0076] 202. Determine the median brightness of a normal image. The median brightness is the median value of the brightness values ​​of the pixels in a normal image.

[0077] In this embodiment of the application, the electronic device can obtain the brightness information of all pixels in a normal image and determine the intermediate brightness, the first brightness, and the second brightness based on the brightness information, wherein the first brightness is higher than the intermediate brightness and the second brightness is lower than the intermediate brightness.

[0078] Optionally, the first and second brightness levels can be set by the developers based on extensive development experience, and are not limited here.

[0079] In one embodiment, the intermediate brightness can be a median value determined based on multiple brightness values ​​corresponding to the pixels included in a normal image. In another optional embodiment, the intermediate brightness can be determined based on a first brightness and a second brightness. It is understood that the brightness of a pixel is typically within the range of 0 to 255, i.e., the brightness value of the brightest pixel is 255, and the brightness value of the darkest pixel is 0. Optionally, the electronic device can first calculate a first difference between the brightness value of the brightest pixel and the brightness value of the first brightness, and calculate a second difference between the brightness value of the second brightness and the brightness value of the darkest pixel, and then determine the median value between the second difference and the first difference as the intermediate brightness.

[0080] For example, assuming the brightness value of the first brightness is X3 and the brightness value of the second brightness is X1, the median value between (255-X3) and (X1-0) can be determined as the intermediate brightness.

[0081] It should be noted that the brightness distribution of image frames at different exposure levels varies. For example, underexposed images are darker, while overexposed images are brighter. Therefore, using the median value of the brightness values ​​of each pixel within an image frame as the median brightness for all images at different exposure levels is inaccurate. To address this, electronic devices can determine a first brightness and a second brightness within the image frame. Based on these first and second brightness values, a more accurate median brightness value can be determined, thus improving the accuracy of the subsequently determined noise reduction parameters.

[0082] Combination Figure 3 For example, Figure 3 This is a schematic diagram of brightness distribution disclosed in an embodiment of this application. The horizontal axis represents the brightness value, and the vertical axis represents the number of pixels corresponding to a certain brightness value; where X1 represents the second brightness, X2 represents the intermediate brightness, and X3 represents the first brightness. It should be further noted that... Figure 3 The illustrations are for illustrative purposes only and should not be construed as limiting the embodiments of this application.

[0083] 204. Obtain a preset set of noise reduction parameters. The set of noise reduction parameters includes the first noise reduction parameter corresponding to the first pixel point with intermediate brightness in the normal image, the third noise reduction parameter corresponding to the third pixel point with first brightness in the normal image, and the fourth noise reduction parameter corresponding to the fourth pixel point with second brightness in the normal image.

[0084] It's understandable that the first noise reduction parameter is a suitable parameter for the mid-brightness of a normal image. Therefore, the effect will not be ideal if the brightness of pixels determined based on the first noise reduction parameter has a large difference from the mid-brightness.

[0085] For example, assuming the intermediate brightness is 100 and the first noise reduction parameter is 10, then the noise reduction parameter corresponding to a pixel with a brightness value of 250 is determined to be 25. In other words, the noise reduction parameter corresponding to a pixel with a brightness value of 250 is only determined by interpolation based on the first noise reduction parameter most suitable for the intermediate brightness. However, the brightness difference between 250 and 100 is too large, so the determined noise reduction parameter of 25 is not the most suitable noise reduction parameter for a pixel with a brightness value of 250, thus hindering the improvement of subsequent noise reduction effects.

[0086] Optionally, the preset noise reduction parameter set also includes a third noise reduction parameter corresponding to the third pixel point with a brightness of the first brightness in the normal image, and a fourth noise reduction parameter corresponding to the fourth pixel point with a brightness of the second brightness in the normal image.

[0087] The third noise reduction parameter can be the noise reduction parameter most suitable for the third pixel with a brightness of the first brightness, and the fourth noise reduction parameter can be the noise reduction parameter most suitable for the fourth pixel with a brightness of the second brightness. Optionally, the third and fourth noise reduction parameters can be set by developers based on extensive development experience, or by the electronic device based on the user's noise reduction requirements; no limitation is imposed here.

[0088] Furthermore, for the second pixel in the overexposed and underexposed images whose brightness is between the first and second brightness levels, since the brightness difference between the second pixel and the first pixel is small, a second noise reduction parameter that is more suitable for the second pixel can be determined using the first noise reduction parameter.

[0089] For the fifth pixel, whose brightness is greater than the first brightness, a more suitable fifth noise reduction parameter can be determined using the third noise reduction parameter; for the sixth pixel, whose brightness is less than the second brightness, a more suitable sixth noise reduction parameter can be determined using the fourth noise reduction parameter. This improves the subsequent noise reduction effect.

[0090] 206. Based on the first noise reduction parameter and the first ratio, determine the second noise reduction parameter for the second pixel point in the overexposed image and the underexposed image whose brightness is between the first brightness and the second brightness.

[0091] In this embodiment, if the preset noise reduction parameter set obtained by the electronic device only includes the first noise reduction parameter, then the second pixel can refer to all pixels in the overexposed and underexposed images. However, if the preset noise reduction parameter set obtained by the electronic device includes the first noise reduction parameter, the third noise reduction parameter, and the fourth noise reduction parameter, then the second pixel can refer to pixels in the overexposed and underexposed images whose brightness is between the first and second brightness levels.

[0092] By implementing the above method, if the preset noise reduction parameter set only includes the first noise reduction parameter, then the noise reduction parameters of other pixels are determined by the first noise reduction parameter. However, if the noise reduction parameter set includes the first noise reduction parameter, the third noise reduction parameter, and the fourth noise reduction parameter, then the noise reduction parameters of pixels with brightness between the first and second brightness can be determined by the first noise reduction parameter alone. The noise reduction parameters of pixels with other brightness can be determined by the third or the fourth noise reduction parameter, thereby improving the accuracy of the subsequently determined noise reduction parameters and increasing the flexibility of the method.

[0093] 208. Determine the fifth noise reduction parameter for the fifth pixel point whose brightness is greater than the first brightness in the overexposed and underexposed images based on the third noise reduction parameter; and determine the sixth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed and underexposed images based on the fourth noise reduction parameter.

[0094] As an optional implementation, the electronic device can determine a fifth noise reduction parameter for a fifth pixel in an overexposed or underexposed image whose brightness is greater than a first brightness, based on a third noise reduction parameter and a second ratio, wherein the second ratio is the ratio between the brightness of the fifth pixel and the brightness of the third pixel.

[0095] By implementing the above method, since the brightness difference between the fifth pixel, which has a brightness greater than the first brightness, and the third pixel, whose brightness is the first brightness, is small, the fifth noise reduction parameter, which is more suitable for the fifth pixel, can be determined based on the third noise reduction parameter that is most suitable for the third pixel, thereby improving the subsequent noise reduction effect.

[0096] Optionally, the electronic device can determine the fifth noise reduction parameter of the fifth pixel in the underexposed image whose brightness is greater than the first brightness based on the third noise reduction parameter; and set the noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness as the target noise reduction parameter, wherein the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0097] It should be noted that overexposed images have a high exposure setting during shooting, resulting in a bright overall image. This often leads to a large brightness value for the fifth pixel in an overexposed image, which is brighter than the first pixel, resulting in a blurry image. Since this fifth pixel may not be used in subsequent HDR image fusion, noise reduction can be omitted for the fifth pixel in an overexposed image, thereby reducing the computational load and power consumption of electronic devices.

[0098] Optionally, the electronic device can set the noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness as the target noise reduction parameter. Then, when the electronic device performs noise reduction processing on the overexposed image, if it determines that the noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness is the target noise reduction parameter, it can choose not to perform noise reduction processing on the fifth pixel in the overexposed image.

[0099] By implementing the above method, the electronic device can set the noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness to the target noise reduction parameter with a noise reduction degree of 0. This can avoid the electronic device from performing noise reduction processing on the fifth pixel that has no value, thereby reducing the computational load and power consumption of the electronic device.

[0100] As another alternative implementation, the electronic device can determine a sixth noise reduction parameter for a sixth pixel in an overexposed or underexposed image whose brightness is less than a second brightness, based on a fourth noise reduction parameter and a third ratio, wherein the third ratio is the ratio between the brightness of the sixth pixel and the brightness of the fourth pixel.

[0101] By implementing the above method, since the brightness difference between the sixth pixel (which has a brightness lower than the second brightness) and the fourth pixel (which has a brightness value of the second brightness) is small, the sixth noise reduction parameter that is more suitable for the sixth pixel can be determined based on the fourth noise reduction parameter that is most suitable for the fourth pixel, thereby improving the subsequent noise reduction effect.

[0102] Optionally, the electronic device can determine the sixth noise reduction parameter of the sixth pixel in the overexposed image whose brightness is less than the second brightness based on the fourth noise reduction parameter; and set the noise reduction parameter of the sixth pixel in the underexposed image whose brightness is less than the second brightness as the target noise reduction parameter, wherein the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0103] It should be noted that underexposed images are usually dark because the exposure setting is low during shooting. As a result, the brightness value of the sixth pixel in the underexposed image, which is less than the second brightness, is usually very small, resulting in an unclear image. Therefore, the sixth pixel may not be used in the subsequent HDR image fusion. For overexposed images, the sixth pixel can be left untreated for noise reduction, thereby reducing the computational load and power consumption of electronic devices.

[0104] Similarly, when an electronic device performs noise reduction on an underexposed image, it may not perform noise reduction on the sixth pixel, whose noise reduction parameter is the target noise reduction parameter.

[0105] By implementing the above method, the electronic device can set the noise reduction parameter of the sixth pixel in the underexposed image, whose brightness is less than the second brightness, to the target noise reduction parameter with a noise reduction degree of 0. This can avoid the electronic device from performing noise reduction processing on the sixth pixel, which has no value, thereby reducing the computational load and power consumption of the electronic device.

[0106] Implementing the methods disclosed in the above embodiments only requires obtaining the first noise reduction parameter of the intermediate brightness of the normal image. That is, the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images can be automatically determined by brightness interpolation, thereby reducing the workload of determining the noise reduction parameter. In addition, since the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images is determined based on the brightness interpolation of each second pixel point, the second noise reduction parameter is more closely matched to the second pixel point, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images. Furthermore, the fifth noise reduction parameter, which is more suitable for the fifth pixel point, can be determined based on the third noise reduction parameter most suitable for the third pixel point, thereby improving the subsequent noise reduction effect. Moreover, the electronic device can avoid performing noise reduction processing on the fifth pixel point, which has no value, thereby reducing the computational load and power consumption of the electronic device. Furthermore, the sixth noise reduction parameter, which is more suitable for the sixth pixel point, can be determined based on the fourth noise reduction parameter most suitable for the fourth pixel point, thereby improving the subsequent noise reduction effect. Moreover, the electronic device can avoid performing noise reduction processing on the sixth pixel point, which has no value, thereby reducing the computational load and power consumption of the electronic device.

[0107] Please see Figure 4 , Figure 4 This is a flowchart illustrating another method for determining noise reduction parameters disclosed in this application. Optionally, this method can be applied to various electronic devices with image processing capabilities, such as mobile phones, tablets, cameras, or smartwatches, etc., and is not limited thereto. Optionally, the method may include the following steps:

[0108] 402. Determine the median brightness of a normal image. The median brightness is the median value of the brightness values ​​of the pixels in a normal image.

[0109] As an optional implementation, when the electronic device determines that the shooting function has been activated, it can further determine the target shooting mode currently in which the electronic device is located; if the target shooting mode is not a barcode scanning mode, it can capture the normal image, overexposed image and underexposed image corresponding to the target scene respectively, and execute step 402.

[0110] Landscape shooting mode or portrait shooting mode are not considered scanning modes. Scanning mode is the mode in which electronic devices use their shooting function to capture information labels such as QR codes and barcodes.

[0111] It is understandable that the image of the QR code to be captured when scanning does not need to be of high quality, so there is no need to use HDR images, thereby reducing the computational load and power consumption of electronic devices. However, if the electronic device is currently in landscape shooting mode or portrait shooting mode, in order to pursue higher image quality, the electronic device can capture HDR images and perform noise reduction processing on the HDR images using the method disclosed in the embodiments of this application.

[0112] 404. Obtain the preset noise reduction parameter set, which includes the first noise reduction parameter corresponding to the first pixel point with intermediate brightness in the normal image.

[0113] As an optional implementation, the electronic device can determine the seventh noise reduction parameter of the seventh pixel in the normal image, excluding the first pixel, based on the first noise reduction parameter and the fourth ratio, where the fourth ratio is the ratio between the brightness of the seventh pixel and the brightness of the first pixel.

[0114] Optionally, the electronic device may determine the noise reduction parameters of pixels in the normal image whose brightness is between the first brightness and the second brightness based on the first noise reduction parameter, determine the noise reduction parameters of pixels in the normal image whose brightness is greater than the first brightness based on the third noise reduction parameter, and determine the noise reduction parameters of pixels in the normal image whose brightness is less than the second brightness based on the fourth noise reduction parameter.

[0115] By implementing the above method, the electronic device can determine the noise reduction parameters suitable for other pixels in the normal image besides the first pixel based on the first noise reduction parameter, thereby reducing the workload of setting the noise reduction parameters while ensuring the subsequent noise reduction effect.

[0116] 406. Based on the first noise reduction parameter and the first ratio, determine the second noise reduction parameter of the second pixel points included in the overexposed image and the underexposed image, wherein the first ratio is the ratio between the brightness of the second pixel point and the brightness of the first pixel point.

[0117] 408. Perform noise reduction processing on the normal image, overexposed image and underexposed image respectively to obtain the target normal image, target overexposed image and target underexposed image, and generate the target high dynamic range image based on the target normal image, target overexposed image and target underexposed image.

[0118] In this embodiment of the application, after determining the noise reduction parameters corresponding to the normal image, overexposed image and underexposed image respectively, the electronic device can perform noise reduction processing on the normal image, overexposed image and underexposed image respectively according to the determined noise reduction parameters to obtain the noise-reduced target normal image, target overexposed image and target underexposed image.

[0119] Optionally, the electronic device can perform noise reduction processing on normal images, overexposed images, and underexposed images respectively using a preset image noise reduction algorithm; wherein the preset image noise reduction algorithm may include, but is not limited to, mean filtering algorithm, Gaussian filtering algorithm, etc.

[0120] Alternatively, the electronic device can fuse the normal image of the target, the overexposed image of the target, and the underexposed image of the target using a preset fusion algorithm to obtain a noise-reduced high dynamic range image of the target; wherein the preset fusion algorithm may include, but is not limited to, a low dynamic range image-aligned fusion algorithm.

[0121] As an optional implementation, after generating a target high dynamic range image based on the target normal image, the target overexposed image, and the target underexposed image, the electronic device can output the target high dynamic range image for user reference and determine whether the remaining capacity of the electronic device's storage space is greater than a capacity threshold. If the remaining capacity of the electronic device's storage space is greater than the capacity threshold, the target high dynamic range image is stored in the electronic device's storage space.

[0122] If the remaining storage capacity of the electronic device is less than or equal to the capacity threshold, the target high dynamic range image can be stored in the cloud server connected to the electronic device. If the electronic device is not connected to a cloud server, a number of normal images less than the target high dynamic range image will be stored in the storage space of the electronic device. This ensures that the storage space of the electronic device is not filled up, and that at least some normal images are stored in the storage space of the electronic device for the user to view later.

[0123] By implementing the above method, the normal image, overexposed image and underexposed image can be denoised according to the determined optimal denoising parameters. Then, the denoised target high dynamic range image can be generated from the denoised target normal image, target overexposed image and target underexposed image, thereby improving the denoising effect of the target high dynamic range image and improving the image quality of the target high dynamic range image.

[0124] Implementing the methods disclosed in the above embodiments only requires obtaining the first noise reduction parameter of the intermediate brightness of the normal image. That is, the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images can be automatically determined by brightness interpolation, thereby reducing the workload of determining the noise reduction parameter. In addition, since the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images is determined based on the brightness interpolation of each second pixel point, the second noise reduction parameter is more closely matched to the second pixel point, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images. Furthermore, the noise reduction parameters suitable for other pixels in the normal image besides the first pixel point can be determined based on the first noise reduction parameter, thereby reducing the workload of setting the noise reduction parameter while ensuring the subsequent noise reduction effect. Moreover, the normal image, overexposed image and underexposed image can be denoised separately according to the determined optimal noise reduction parameters, and then the denoised target high dynamic range image can be generated based on the denoised target normal image, target overexposed image and target underexposed image, thereby improving the noise reduction effect of the target high dynamic range image and improving the image quality of the target high dynamic range image.

[0125] Please see Figure 5 , Figure 5 This is a schematic diagram of a noise reduction parameter determination device disclosed in an embodiment of this application. Optionally, this device can be applied to various electronic devices with image processing capabilities, such as mobile phones, tablets, cameras, or smartwatches, etc., and is not limited thereto. Optionally, the device may include a first determining unit 502, an acquiring unit 504, and a second determining unit 506, wherein:

[0126] The first determining unit 502 is used to determine the median brightness of a normal image, where the median brightness is the median value of multiple brightness values ​​corresponding to the pixels in the normal image.

[0127] The acquisition unit 504 is used to acquire a preset set of noise reduction parameters, which includes the first noise reduction parameter corresponding to the first pixel point with intermediate brightness in the normal image.

[0128] The second determining unit 506 is used to determine the second noise reduction parameters of the second pixels included in the overexposed image and the underexposed image according to the first noise reduction parameters and the first ratio, wherein the first ratio is the ratio between the brightness of the second pixel and the brightness of the first pixel.

[0129] By implementing the above apparatus, the median brightness of the normal image used to synthesize the high dynamic range image can be determined first. The median brightness is the median value of multiple brightness values ​​corresponding to the pixels in the normal image. Then, a preset set of noise reduction parameters can be obtained. The set of noise reduction parameters can at least include the first noise reduction parameter corresponding to the first pixel in the normal image with the median brightness. Then, based on the first noise reduction parameter and the second ratio, the second noise reduction parameter of the second pixel in the overexposed and underexposed images used to synthesize the high dynamic range image can be determined. The first ratio is the ratio of the brightness of the second pixel to the brightness of the first pixel. As can be seen, by implementing the embodiments of this application, it is only necessary to obtain the first noise reduction parameter of the intermediate brightness of the normal image. That is, the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images can be automatically determined by brightness interpolation, thereby reducing the workload of determining the noise reduction parameter. In addition, since the second noise reduction parameter of each second pixel point included in the overexposed and underexposed images is determined based on the brightness interpolation of each second pixel point, the second noise reduction parameter is more closely matched to the second pixel point, thereby improving the subsequent noise reduction effect on the overexposed and underexposed images.

[0130] As an optional implementation, the noise parameter set further includes a third noise reduction parameter corresponding to a third pixel in the normal image with a brightness of a first brightness, and a fourth noise reduction parameter corresponding to a fourth pixel in the normal image with a brightness of a second brightness, wherein the first brightness is higher than the intermediate brightness and the second brightness is lower than the intermediate brightness; and the second determining unit 506 is further configured to determine a second noise reduction parameter for a second pixel in the overexposed and underexposed images with a brightness between the first and second brightness, based on the first noise reduction parameter and the first ratio; determine a fifth noise reduction parameter for a fifth pixel in the overexposed and underexposed images with a brightness greater than the first brightness, based on the third noise reduction parameter; and determine a sixth noise reduction parameter for a sixth pixel in the overexposed and underexposed images with a brightness less than the second brightness, based on the fourth noise reduction parameter.

[0131] By implementing the above method, the noise reduction parameters of pixels with brightness between the first and second brightness levels can be determined using only the first noise reduction parameter. The noise reduction parameters of pixels with other brightness levels can be determined by the third or fourth noise reduction parameter, thereby improving the accuracy of the subsequently determined noise reduction parameters and increasing the flexibility of the method.

[0132] As an optional implementation, the second determining unit 506 is further configured to determine a fifth noise reduction parameter for a fifth pixel in the overexposed and underexposed images whose brightness is greater than a first brightness, based on a third noise reduction parameter and a second ratio, wherein the second ratio is the ratio between the brightness of the fifth pixel and the brightness of the third pixel; and to determine a sixth noise reduction parameter for a sixth pixel in the overexposed and underexposed images whose brightness is less than a second brightness, based on a fourth noise reduction parameter and a third ratio, wherein the third ratio is the ratio between the brightness of the sixth pixel and the brightness of the fourth pixel.

[0133] By implementing the above apparatus, a fifth noise reduction parameter more suitable for the fifth pixel can be determined based on the third noise reduction parameter most suitable for the third pixel, thereby improving the subsequent noise reduction effect; and a sixth noise reduction parameter more suitable for the sixth pixel can be determined based on the fourth noise reduction parameter most suitable for the fourth pixel, thereby improving the subsequent noise reduction effect.

[0134] As an optional implementation, the second determining unit 506 is further configured to determine a fifth noise reduction parameter for a fifth pixel in an underexposed image whose brightness is greater than the first brightness, based on a third noise reduction parameter; and to set the noise reduction parameter for a fifth pixel in an overexposed image whose brightness is greater than the first brightness as a target noise reduction parameter, wherein the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0135] By implementing the above device, the noise reduction parameter of the fifth pixel in an overexposed image whose brightness is greater than the first brightness can be set to the target noise reduction parameter with a noise reduction degree of 0. This can prevent the electronic device from performing noise reduction processing on the fifth pixel that has no value, thereby reducing the computational load and power consumption of the electronic device.

[0136] As an optional implementation, the second determining unit 506 is further configured to determine a sixth noise reduction parameter for a sixth pixel in an overexposed image whose brightness is less than the second brightness, based on the fourth noise reduction parameter; and to set the noise reduction parameter for a sixth pixel in an underexposed image whose brightness is less than the second brightness as a target noise reduction parameter, wherein the noise reduction degree corresponding to the target noise reduction parameter is 0.

[0137] By implementing the above device, the noise reduction parameter of the sixth pixel in the underexposed image whose brightness is less than the second brightness can be set to the target noise reduction parameter with a noise reduction degree of 0. This can prevent the electronic device from performing noise reduction processing on the sixth pixel that has no value, thereby reducing the computational load and power consumption of the electronic device.

[0138] As an optional implementation method, Figure 5 The apparatus shown may further include a third determining unit (not shown), wherein:

[0139] The third determining unit is used to determine the seventh noise reduction parameter of the seventh pixel in the normal image, excluding the first pixel, based on the first noise reduction parameter and the fourth ratio, after obtaining a preset set of noise reduction parameters. The fourth ratio is the ratio between the brightness of the seventh pixel and the brightness of the first pixel.

[0140] By implementing the above device, the noise reduction parameters suitable for other pixels in the normal image besides the first pixel can be determined based on the first noise reduction parameter, thereby reducing the workload of setting the noise reduction parameters while ensuring the subsequent noise reduction effect.

[0141] As an optional implementation method, Figure 5 The apparatus shown may further include a noise reduction unit and a generation unit (not shown), wherein:

[0142] The noise reduction unit is used to perform noise reduction processing on the normal image, the overexposed image and the underexposed image respectively after determining the second noise reduction parameters of the second pixels included in the overexposed image and the underexposed image according to the first noise reduction parameters and the first ratio, so as to obtain the target normal image, the target overexposed image and the target underexposed image.

[0143] The generation unit is used to generate a high dynamic range image of the target based on the normal image of the target, the overexposed image of the target, and the underexposed image of the target.

[0144] By implementing the above device, noise reduction can be performed on normal images, overexposed images, and underexposed images respectively according to the determined optimal noise reduction parameters. Then, a noise-reduced target high dynamic range image can be generated based on the noise-reduced target normal image, target overexposed image, and target underexposed image, thereby improving the noise reduction effect of the target high dynamic range image and improving the image quality of the target high dynamic range image.

[0145] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0146] like Figure 6 As shown, the electronic device may include:

[0147] Memory 601 storing executable program code;

[0148] Processor 602 coupled to memory 601;

[0149] The processor 602 calls the executable program code stored in the memory 601 to execute the noise reduction parameter determination method disclosed in the above embodiments.

[0150] This application discloses a computer-readable storage medium storing a computer program that causes a computer to execute the noise reduction parameter determination method disclosed in the above embodiments.

[0151] This application also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer performs some or all of the steps of the methods described in the above method embodiments.

[0152] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Those skilled in the art should also recognize that the embodiments described in the specification are optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0153] In the various embodiments of this application, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0154] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0156] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-accessible memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of this application.

[0157] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0158] The above provides a detailed description of a method, apparatus, electronic device, and storage medium for determining noise reduction parameters disclosed in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for determining noise reduction parameters, characterized in that, A high dynamic range image is generated from a normal image, an overexposed image, and an underexposed image, wherein the exposure value corresponding to the overexposed image is greater than the exposure value corresponding to the normal image, and the exposure value corresponding to the underexposed image is less than the exposure value corresponding to the normal image. The method includes: Determine the median brightness of the normal image, wherein the median brightness is the median value of multiple brightness values ​​corresponding to the pixels included in the normal image; Obtain a preset set of noise reduction parameters, the set of noise reduction parameters including the first noise reduction parameter corresponding to the first pixel point in the normal image whose brightness is the intermediate brightness; Based on the first noise reduction parameter and the first ratio, a second noise reduction parameter is determined for the second pixel points included in the overexposed image and the underexposed image, wherein the first ratio is the ratio between the brightness of the second pixel point and the brightness of the first pixel point; The noise reduction parameter set also includes a third noise reduction parameter corresponding to a third pixel in the normal image with a brightness of a first brightness, and a fourth noise reduction parameter corresponding to a fourth pixel in the normal image with a brightness of a second brightness, wherein the first brightness is higher than the intermediate brightness and the second brightness is lower than the intermediate brightness. The step of determining the second noise reduction parameter for the second pixels included in the overexposed image and the underexposed image based on the first noise reduction parameter and the first ratio includes: Based on the first noise reduction parameter and the first ratio, a second noise reduction parameter is determined for the second pixel point in the overexposed image and the underexposed image whose brightness is between the first brightness and the second brightness. The fifth noise reduction parameter is determined based on the third noise reduction parameter for the fifth pixel point in the overexposed image and the underexposed image whose brightness is greater than the first brightness. The sixth noise reduction parameter is determined based on the fourth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image.

2. The method according to claim 1, characterized in that, The step of determining the fifth noise reduction parameter for the fifth pixel point whose brightness is greater than the first brightness in the overexposed image and the underexposed image based on the third noise reduction parameter includes: Based on the third noise reduction parameter and the second ratio, a fifth noise reduction parameter is determined for the fifth pixel in the overexposed image and the underexposed image whose brightness is greater than the first brightness. The second ratio is the ratio between the brightness of the fifth pixel and the brightness of the third pixel. And, determining the sixth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image based on the fourth noise reduction parameter includes: Based on the fourth noise reduction parameter and the third ratio, a sixth noise reduction parameter is determined for the sixth pixel in the overexposed image and the underexposed image whose brightness is less than the second brightness. The third ratio is the ratio between the brightness of the sixth pixel and the brightness of the fourth pixel.

3. The method according to claim 1 or 2, characterized in that, The step of determining the fifth noise reduction parameter for the fifth pixel point whose brightness is greater than the first brightness in the overexposed image and the underexposed image based on the third noise reduction parameter includes: The fifth noise reduction parameter is determined based on the third noise reduction parameter for the fifth pixel in the underexposed image whose brightness is greater than the first brightness. The noise reduction parameter of the fifth pixel in the overexposed image whose brightness is greater than the first brightness is set as the target noise reduction parameter, and the noise reduction degree corresponding to the target noise reduction parameter is 0.

4. The method according to claim 1 or 2, characterized in that, The step of determining the sixth noise reduction parameter for the sixth pixel point whose brightness is less than the second brightness in the overexposed image and the underexposed image according to the fourth noise reduction parameter includes: The sixth noise reduction parameter is determined based on the fourth noise reduction parameter for the sixth pixel in the overexposed image whose brightness is less than the second brightness. The noise reduction parameter of the sixth pixel in the underexposed image whose brightness is less than the second brightness is set as the target noise reduction parameter, and the noise reduction degree corresponding to the target noise reduction parameter is 0.

5. The method according to claim 1, characterized in that, After obtaining the preset set of noise reduction parameters, the method further includes: Based on the first noise reduction parameter and the fourth ratio, the seventh noise reduction parameter of the seventh pixel in the normal image, excluding the first pixel, is determined, wherein the fourth ratio is the ratio between the brightness of the seventh pixel and the brightness of the first pixel.

6. The method according to claim 1, characterized in that, After determining the second noise reduction parameters for the second pixels included in the overexposed image and the underexposed image based on the first noise reduction parameters and the first ratio, the method further includes: The normal image, overexposed image, and underexposed image are respectively subjected to noise reduction processing to obtain the target normal image, target overexposed image, and target underexposed image; A high dynamic range image of the target is generated based on the normal image of the target, the overexposed image of the target, and the underexposed image of the target.

7. A device for determining noise reduction parameters, characterized in that, A high dynamic range image is generated from a normal image, an overexposed image, and an underexposed image, wherein the exposure value corresponding to the overexposed image is greater than the exposure value corresponding to the normal image, and the exposure value corresponding to the underexposed image is less than the exposure value corresponding to the normal image. The device includes: The first determining unit is used to determine the median brightness of the normal image, wherein the median brightness is the median value of multiple brightness values ​​corresponding to the pixels included in the normal image. The acquisition unit is used to acquire a preset set of noise reduction parameters. The set of noise reduction parameters includes a first noise reduction parameter corresponding to a first pixel in the normal image with a brightness of the intermediate brightness, a third noise reduction parameter corresponding to a third pixel in the normal image with a brightness of the first brightness, and a fourth noise reduction parameter corresponding to a fourth pixel in the normal image with a brightness of the second brightness. The first brightness is higher than the intermediate brightness, and the second brightness is lower than the intermediate brightness. The second determining unit is configured to determine, based on the first noise reduction parameter and the first ratio, a second noise reduction parameter for a second pixel in the overexposed image and the underexposed image whose brightness is between the first brightness and the second brightness; a fifth noise reduction parameter for a fifth pixel in the overexposed image and the underexposed image whose brightness is greater than the first brightness; and a sixth noise reduction parameter for a sixth pixel in the overexposed image and the underexposed image whose brightness is less than the second brightness, based on the fourth noise reduction parameter, wherein the first ratio is the ratio between the brightness of the second pixel and the brightness of the first pixel.

8. An electronic device, characterized in that, The method includes a memory storing executable program code and a processor coupled to the memory; wherein the processor invokes the executable program code stored in the memory to perform the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 6.

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