Image processing method, apparatus and device

Abstract

Embodiments of the present application provide an image processing method, device and equipment. The method comprises: obtaining a first set compression ratio and a first actual compression ratio of a first image; obtaining a content complexity of a second image, the second image being a next frame image of the first image; determining a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and compressing the second image according to the second set compression ratio. The image quality of the video after the time domain noise reduction processing is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of computer, and particularly relate to an image processing method, device and equipment. BACKGROUND

[0002] In the process of image acquisition, transmission and processing, different degrees of noise will be introduced, and therefore, 3-dimensional noise reduction (3DNR) processing is needed for pictures. 3DNR mainly includes spatial domain noise reduction and time domain noise reduction, wherein, the spatial domain noise reduction refers to noise reduction within the current frame range by using spatial correlation, and the time domain noise reduction refers to filtering the current frame and the previous frame data to achieve the purpose of noise reduction by using time correlation.

[0003] In the related art, the time domain noise reduction manner can be used to perform noise reduction processing on a video. Assuming that a certain video has N frames, wherein N is any positive integer greater than or equal to 2. When the time domain noise reduction manner is used to process the Nth image, the N-1th image stored in the DDR display memory is usually needed, which is an image that has been processed by time domain noise reduction. However, in order to save system bandwidth, the N-1th image in the DDR display memory is usually a compressed image. The N-1th image after compression will introduce compression errors when participating in the time domain noise reduction processing of the Nth image, thereby causing the image quality of the Nth image after time domain noise reduction processing to decrease. SUMMARY

[0004] Embodiments of the present application provide an image processing method, device and equipment, which improve the image quality of the video after time domain noise reduction processing.

[0005] In a first aspect, embodiments of the present application provide an image processing method, comprising:

[0006] obtaining a first set compression ratio and a first actual compression ratio of a first image;

[0007] obtaining a content complexity of a second image, the second image being a next frame image of the first image;

[0008] determining a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and performing compression processing on the second image according to the second set compression ratio.

[0009] In a possible implementation, determining the second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity comprises:

[0010] if the content complexity is greater than a first threshold and less than a second threshold, determining the second set compression ratio as a default compression ratio, the second threshold being greater than the first threshold;

[0011] if the content complexity is less than or equal to the first threshold, or the content complexity is greater than or equal to the second threshold, determining the second set compression ratio according to the first set compression ratio and the first actual compression ratio.

[0012] In a possible implementation, the content complexity is less than or equal to the first threshold; and determining the second set compression ratio according to the first set compression ratio and the first actual compression ratio comprises:

[0013] if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second set compression ratio as the default compression ratio;

[0014] if the first set compression ratio is greater than the first actual compression ratio, determining the second set compression ratio as a product of the first adjustment coefficient and the default compression ratio, the first adjustment coefficient being greater than or equal to 1.

[0015] In a possible implementation, the first adjustment coefficient is greater than or equal to 1 and less than or equal to 2.

[0016] In a possible implementation, the content complexity is greater than or equal to the second threshold; and determining the second set compression ratio according to the first set compression ratio and the first actual compression ratio comprises:

[0017] if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second set compression ratio as a product of the second adjustment coefficient and the default compression ratio, the second adjustment coefficient being less than or equal to 1;

[0018] if the first set compression ratio is greater than the first actual compression ratio, determining the second set compression ratio as the default compression ratio.

[0019] In a possible implementation, the second adjustment coefficient is greater than or equal to 0.5 and less than or equal to 1.

[0020] In a possible implementation, obtaining the content complexity of the second image comprises:

[0021] obtaining a gray value of each pixel in the second image;

[0022] determining a variance value corresponding to the second image according to the gray value of each pixel in the second image;

[0023] determine a content complexity of the second image according to the variance value corresponding to the second image.

[0024] In a possible implementation, the compressing the second image according to the second set compression ratio comprises:

[0025] obtaining the first image compressed in the DDR display memory;

[0026] decompressing the first image;

[0027] performing three-dimensional noise reduction on the second image by using the decompressed first image to obtain a second image after noise reduction;

[0028] compressing the second image after noise reduction by using the second set compression ratio.

[0029] In a possible implementation, after the compressing the second image according to the second set compression ratio, the method further comprises:

[0030] storing the compressed second image to the DDR display memory.

[0031] In a second aspect, an embodiment of the present application provides an image processing apparatus, comprising a first obtaining module, a second obtaining module, a determining module and a compressing module, wherein,

[0032] The first obtaining module is configured to obtain a first set compression ratio and a first actual compression ratio of a first image.

[0033] The second obtaining module is configured to obtain a content complexity of a second image, the second image being a next frame image of the first image.

[0034] The determining module is configured to determine a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity.

[0035] The compressing module is configured to compress the second image according to the second set compression ratio.

[0036] In a possible implementation, the determining module is specifically configured to:

[0037] if the content complexity is greater than a first threshold value and less than a second threshold value, determining the second set compression ratio as a default compression ratio, the second threshold value being greater than the first threshold value.

[0038] If the content complexity is less than or equal to the first threshold value or greater than or equal to the second threshold value, the second set compression ratio is determined according to the first set compression ratio and the first actual compression ratio.

[0039] In a possible implementation, the determining module is specifically configured to:

[0040] If the first set compression ratio is less than or equal to the first actual compression ratio, the second set compression ratio is determined as a product of the first adjustment coefficient and the default compression ratio, the first adjustment coefficient being greater than or equal to 1.

[0041] If the first set compression ratio is greater than the first actual compression ratio, the second set compression ratio is determined as a product of the first adjustment coefficient and the default compression ratio, the first adjustment coefficient being greater than or equal to 1.

[0042] In a possible implementation, the determining module is specifically configured to:

[0043] The first adjustment coefficient is greater than or equal to 1 and less than or equal to 2.

[0044] In a possible implementation, the determining module is specifically configured to:

[0045] If the first set compression ratio is less than or equal to the first actual compression ratio, the second set compression ratio is determined as a product of the second adjustment coefficient and the default compression ratio, the second adjustment coefficient being less than or equal to 1.

[0046] If the first set compression ratio is greater than the first actual compression ratio, the second set compression ratio is determined as the default compression ratio.

[0047] In a possible implementation, the determining module is specifically configured to:

[0048] The second adjustment coefficient is greater than or equal to 0.5 and less than or equal to 1.

[0049] In a possible implementation, the second obtaining module is specifically configured to:

[0050] Obtain the gray value of each pixel in the second image.

[0051] Determine the variance value corresponding to the second image according to the gray value of each pixel in the second image.

[0052] Determine the content complexity of the second image according to the variance value corresponding to the second image.

[0053] In a possible implementation, the compressing module is specifically configured to:

[0054] acquire the first image compressed by the compression processing from the DDR memory;

[0055] decompress the first image;

[0056] perform three-dimensional noise reduction processing on the second image by using the first image after the decompression processing to obtain a second image after the noise reduction processing;

[0057] perform compression processing on the second image after the noise reduction processing by using the second set compression ratio.

[0058] In a possible implementation, the image processing apparatus further includes a storage module.

[0059] The storage module is configured to store the second image after the compression processing to the DDR memory.

[0060] In a third aspect, an embodiment of the present application provides an image processing device, including a processor and a memory.

[0061] The memory is configured to store a computer program.

[0062] The processor is configured to execute the computer program stored in the memory to implement the method in any one of the first aspect.

[0063] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer execution instructions, and the computer execution instructions are configured to implement the method in any one of the first aspect when executed by a processor.

[0064] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program, and the computer program is configured to implement the method in any one of the first aspect when executed by a processor.

[0065] The image processing method, apparatus and device provided in the embodiments of the present application can acquire a first set compression ratio and a first actual compression ratio of a first image, acquire a content complexity of a second image, and determine a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and perform compression processing on the second image according to the second set compression ratio. In the above process, the set compression ratio of each frame of image in the time domain noise reduction processing process can be adaptively adjusted to reduce the compression error in the time domain noise reduction processing process, and the image quality of the video after the time domain noise reduction processing is effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0066] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0067] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application is shown in

[0068] Figure 2 A flowchart of an image processing method provided for an embodiment of the present application is shown in

[0069] Figure 3 A flowchart of another image processing method provided for an embodiment of the present application is shown in

[0070] Figure 4 A process diagram of obtaining a second set compression ratio of a second image provided for an embodiment of the present application is shown in

[0071] Figure 5 A process diagram of three-dimensional noise reduction processing, compression processing and storage of a second image provided for an embodiment of the present application is shown in

[0072] Figure 6 A structural diagram of an image processing apparatus provided for an embodiment of the present application is shown in

[0073] Figure 7 Another structural diagram of an image processing apparatus provided for an embodiment of the present application is shown in

[0074] Figure 8 A hardware structural diagram of an image processing device provided for an embodiment of the present application is shown in

[0075] The specific embodiments of the present application have been shown through the above-described drawings, and will be described in more detail hereinafter. These drawings and the written description are not intended to restrict the scope of the present application concept in any way, but to illustrate the present application concept to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0076] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some, but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0077] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application is shown in Figure 1The image processing device 101 can adaptively adjust the set compression ratio to compress the image after 3D noise reduction and store the compressed image in DDR video memory.

[0078] In related technologies, temporal denoising can be used to denoise video. Assume a video has N frames, where N is any positive integer greater than or equal to 2. When processing the Nth frame using temporal denoising, the (N-1)th frame stored in DDR video memory is typically used; this (N-1)th frame has already undergone temporal denoising. However, to save system bandwidth, the (N-1)th frame in DDR video memory is usually compressed. This compressed (N-1)th frame introduces compression errors during the temporal denoising process of the Nth frame, resulting in a decrease in the image quality of the Nth frame after temporal denoising.

[0079] In this embodiment, the compression ratio of each frame in the video can be adaptively adjusted based on the content complexity of each frame and the first set compression ratio and the first actual compression ratio of the previous frame, thereby reducing the compression error in the temporal denoising process and effectively improving the image quality of the video after temporal denoising.

[0080] The method described in this application will now be illustrated through specific embodiments. It should be noted that the following embodiments may exist independently or in combination with each other; identical or similar content will not be repeated in different embodiments.

[0081] Figure 2 This is a schematic flowchart illustrating an image processing method provided in an embodiment of this application. Please refer to [link / reference]. Figure 2 The method may include:

[0082] S201. Obtain the first set compression ratio and the first actual compression ratio of the first image.

[0083] The execution subject of this application embodiment can be an image processing device or an image processing apparatus disposed within an image processing device. The image processing apparatus can be implemented by software or by a combination of software and hardware.

[0084] For any given video, suppose the video has N frames, where N is any positive integer greater than or equal to 1. The first frame can be any frame from the video.

[0085] Optionally, the first set compression ratio can be a compression ratio set for the first image according to a preset manner before the first image is compressed. For example, the first set compression ratio can be 2. If the first image is a first frame image in a video, the first set compression ratio of the first image can be a default compression ratio of the system.

[0086] The actual compression ratio of the first image can be obtained by: obtaining an image data amount before the first image is compressed and an image data amount after the first image is compressed; and determining a ratio of the image data amount before the first image is compressed to the image data amount after the first image is compressed as the actual compression ratio of the first image.

[0087] The actual compression ratio of the first image can be calculated by the following formula:

[0088]

[0089] For example, the image data amount before the first image is compressed is 200 KB, and the image data amount after the first image is compressed is 20 KB. Thus, the actual compression ratio of the first image is 10.

[0090] S202, obtaining a content complexity of a second image.

[0091] The second image is a next frame image of the first image. For example, the first image is a first frame image, and the second image is a second frame image.

[0092] The content complexity of the second image can be obtained by: obtaining gray values of each pixel in the second image; determining a variance value corresponding to the second image according to the gray values of each pixel in the second image; and determining the content complexity of the second image according to the variance value corresponding to the second image.

[0093] Optionally, the content complexity of the second image can be determined by a preset threshold. Assuming that there are two preset thresholds, a first threshold (Thr0) and a second threshold (Thr1), and Thr1 is greater than Thr0. Then, a value range of the variance value of the second image can be divided into three ranges according to Thr0 and Thr1, and the content complexity of the second image can be divided into three levels according to the value range of the variance value. The specific division is shown in Table 1.

[0094] Table 1

[0095] Range of values of the variance value Content complexity level Content complexity case Variance value < Thr0 Level 0 Simple content Thr0 < Variance value < Thr1 Level 1 Comparatively complex content Variance value > Thr1 Level 2 Complex content

[0096] Please see Table 1, when the variance value of the second image belongs to the value range of variance value ≤Thr0, the content complexity level corresponding to the second image is 0, indicating that the content of the second image is simple; when the variance value of the second image belongs to the value range of Thr0 < variance value < Thr1, the content complexity level corresponding to the second image is 1, indicating that the content of the second image is relatively complex; when the variance value of the second image belongs to the value range of variance value ≥Thr1, the content complexity level corresponding to the second image is 2, indicating that the content of the second image is complex.

[0097] S203, determining a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and performing compression processing on the second image according to the second set compression ratio.

[0098] The second set compression ratio of the second image can be determined in the following manner: if the content complexity is greater than a first threshold and less than a second threshold, the second set compression ratio is determined as a default compression ratio, the second threshold being greater than the first threshold; if the content complexity is less than or equal to the first threshold, or the content complexity is greater than or equal to the second threshold, the second set compression ratio is determined according to the first set compression ratio and the first actual compression ratio.

[0099] The image processing method, device and equipment provided by the embodiments of the present application can obtain the first set compression ratio and the first actual compression ratio of the first image, obtain the content complexity of the second image which is the next frame image of the first image, determine the second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and perform compression processing on the second image according to the second set compression ratio. In the above process, the set compression ratio of each frame image in the time domain noise reduction processing process can be adaptively adjusted to reduce the compression error in the time domain noise reduction processing process, thereby effectively improving the image quality of the video after time domain noise reduction processing.

[0100] On the basis of any one of the above embodiments, the following will be described in combination with Figure 3 The detailed process of the image processing method will be described.

[0101] Figure 3 The flowchart of another image processing method provided by the embodiments of the present application is shown in FIG. 3. Please see FIG. 3, the method can include the following steps. Figure 3

[0102] S301, obtaining the first set compression ratio and the first actual compression ratio of the first image.

[0103] It should be noted that the execution process of S301 can refer to the execution process of S201, which will not be described here.

[0104] ​S302, acquire the gray value of each pixel in the second image.

[0105] Optionally, the second image can be processed based on a commonly used image processing software to acquire the gray value of each pixel in the second image. For example, the image processing software can be OpenCV software or python software, etc.

[0106] S303, determine the variance value corresponding to the second image according to the gray value of each pixel in the second image.

[0107] Optionally, the gray value of each pixel in the second image can be processed based on a commonly used data processing software to determine the variance value corresponding to the second image. For example, the data processing software can be Matlab software.

[0108] S304, determine the content complexity of the second image according to the variance value corresponding to the second image.

[0109] The process of S302-S304 can be performed for each second image to obtain the second content complexity of each second image.

[0110] Next, the second set compression ratio of the second image is determined in combination with the content complexity of the second image and the first set compression ratio and the first actual compression ratio of the first image.

[0111] S305, determine the relationship between the content complexity of the second image and the first threshold value and the second threshold value.

[0112] In actual application, the set compression ratio of the second image can be adaptively adjusted based on the content complexity of the second image,

[0113] The relationship between the content complexity of the second image and the first threshold value and the second threshold value can be as follows:

[0114] Case 1: the content complexity of the second image is less than or equal to the first threshold value;

[0115] Case 2: the content complexity of the second image is greater than the first threshold value and less than the second threshold value;

[0116] Case 3: the content complexity of the second image is greater than or equal to the second threshold value.

[0117] If it is the relationship shown in case 1, S306-S308 are executed; if it is the relationship shown in case 2, S309 is executed; if it is the relationship shown in case 3, S310-S312 are executed.

[0118] Next, the process of determining the second set compression ratio is described in combination with S306-S308 for the relationship shown in case 1.

[0119] S306, if the content complexity is less than or equal to the first threshold, determining the relationship between the first set compression ratio and the first actual compression ratio.

[0120] S307, if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second set compression ratio as the default compression ratio.

[0121] S308, if the first set compression ratio is greater than the first actual compression ratio, determining the second set compression ratio as the product of the first adjustment coefficient and the default compression ratio.

[0122] The first adjustment coefficient is greater than or equal to 1 and less than or equal to 2.

[0123] For example, the default compression ratio is 2 and the first adjustment coefficient is 1.2, then the second set compression ratio is 2.4.

[0124] Next, in combination with S309, the process of determining the second set compression ratio is described for the relationship shown in case 2.

[0125] S309, if the content complexity is greater than the first threshold and less than the second threshold, determining the second set compression ratio as the default compression ratio.

[0126] Next, in combination with S310-S312, the process of determining the second set compression ratio is described for the relationship shown in case 3.

[0127] S310, if the content complexity is greater than or equal to the second threshold, determining the relationship between the first set compression ratio and the first actual compression ratio.

[0128] S311, if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second set compression ratio as the product of the second adjustment coefficient and the default compression ratio.

[0129] The second adjustment coefficient is greater than or equal to 0.5 and less than or equal to 1.

[0130] For example, the default compression ratio is 2 and the second adjustment coefficient is 0.8, then the second set compression ratio is 1.6.

[0131] S312, if the first set compression ratio is greater than the first actual compression ratio, determining the second set compression ratio as the default compression ratio.

[0132] The process of S301-S312 is performed for each second image, and the second set compression ratio of each second image can be obtained.

[0133] Next, in combination with S313-S315, the process of obtaining the second image after noise reduction processing is described.

[0134] S313, acquire the first image which has been compressed in a double data rate (DDR) memory.

[0135] S314, decompress the first image.

[0136] S315, perform three-dimensional noise reduction on the second image by using the first image which has been decompressed to obtain a second image which has been reduced in noise.

[0137] Optionally, the three-dimensional noise reduction result and the filter intensity coefficient of the first image which has been decompressed can be acquired, and then the three-dimensional noise reduction is performed on the second image according to the three-dimensional noise reduction result and the filter intensity coefficient.

[0138] S316, compress the second image which has been reduced in noise by using a second set compression ratio.

[0139] S317, store the second image which has been compressed in the DDR memory.

[0140] The image processing method, device and equipment provided by the embodiment can acquire a first set compression ratio and a first actual compression ratio of a first image, acquire a content complexity of a second image which is a next frame image of the first image, determine a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity, and compress the second image according to the second set compression ratio. In the above process, the set compression ratio of each frame image in the time domain noise reduction process can be adaptively adjusted to reduce the compression error in the time domain noise reduction process, and the image quality of the video which has been reduced in noise is effectively improved.

[0141] In the following, the process of acquiring the second set compression ratio of the second image is described in combination with Figure 4

[0142] Figure 4 The process of acquiring the second set compression ratio of the second image provided by the embodiment is shown in the following figure. Please refer to Figure 4 The content complexity of the second image can be acquired first, and the level of the content complexity of the second image is determined according to the first threshold and the second threshold. The content complexity of the second image has three levels, i.e. 0 level, 1 level and 2 level.

[0143] It can be seen that when the content complexity of the second image is 1 level, the second set compression ratio of the second image, i.e. the default compression ratio, can be directly acquired. When the content complexity of the second image is 0 level and 2 level, the second set compression ratio needs to be further acquired in combination with the first actual compression ratio and the first set compression ratio of the first image.

[0144] ​When the content complexity of the second image is level 0: if the first actual compression ratio of the first image is greater than the first set compression ratio, the default compression ratio needs to be corrected by the first adjustment coefficient to obtain the second compression; if the first actual compression ratio of the first image is less than or equal to the first set compression ratio, the second set compression ratio of the second image, i.e., the default compression ratio, can be obtained directly.

[0145] When the content complexity of the second image is level 2: if the first actual compression ratio of the first image is greater than the first set compression ratio, the second set compression ratio of the second image, i.e., the default compression ratio, can be obtained directly; if the first actual compression ratio of the first image is less than or equal to the first set compression ratio, the default compression ratio needs to be corrected by the second adjustment coefficient to obtain the second set compression ratio.

[0146] In the process of obtaining the second set compression ratio of the second image, this application embodiment can adaptively adjust the second set compression ratio of the second image by combining the content complexity of the second image with the first actual compression ratio and the first set compression ratio of the first image, which can effectively alleviate the pressure on system bandwidth when storing the second image.

[0147] Below, in conjunction with Figure 5 The process of three-dimensional noise reduction, compression, and storage of the second image is explained.

[0148] Figure 5 This is a schematic diagram illustrating the process of three-dimensional noise reduction, compression, and storage of the second image provided in an embodiment of this application. Please refer to... Figure 5 First, a denoised and compressed first image is retrieved from DDR video memory. This image is then decompressed using a decompression module to obtain a denoised first image. Combining the 3D denoising result of the denoised first image, a 3D denoising module performs 3D denoising on the undenoised second image to obtain a denoised second image. This denoised second image is then compressed using a compression module to obtain a denoised and compressed second image, which is finally stored in DDR video memory.

[0149] The method provided in this application embodiment can perform three-dimensional noise reduction, compression, and storage of a second image. Therefore, it is applicable to image processing chips or image processing devices related to image acquisition, image post-processing, and image display. For example, the image processing device can be a camera, an image processing platform, and a display device.

[0150] Figure 6 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of this application. Please refer to... Figure 6 The image processing device 10 includes a first acquisition module 11, a second acquisition module 12, a determination module 13, and a compression module 14, wherein...

[0151] The first acquisition module 11 is configured to acquire a first set compression ratio and a first actual compression ratio of a first image.

[0152] The second acquisition module 12 is configured to acquire a content complexity of a second image, the second image being a next frame image of the first image.

[0153] The determination module 13 is configured to determine a second set compression ratio of the second image according to the first set compression ratio, the first actual compression ratio and the content complexity.

[0154] The compression module 14 is configured to perform compression processing on the second image according to the second set compression ratio.

[0155] The image processing apparatus provided by the embodiments of the present application can implement the technical solutions shown in the method embodiments, and the implementation principles and beneficial effects are similar, which will not be repeated here.

[0156] In a possible implementation, the determination module 13 is specifically configured to:

[0157] If the content complexity is greater than a first threshold and less than a second threshold, the second compression ratio is determined as a default compression ratio, the second threshold being greater than the first threshold.

[0158] If the content complexity is less than or equal to the first threshold, or the content complexity is greater than or equal to the second threshold, the second set compression ratio is determined according to the first set compression ratio and the first actual compression ratio.

[0159] In a possible implementation, the determination module 13 is specifically configured to:

[0160] If the first set compression ratio is less than or equal to the first actual compression ratio, the second set compression ratio is determined as the default compression ratio.

[0161] If the first set compression ratio is greater than the first actual compression ratio, the second set compression ratio is determined as a product of the first adjustment coefficient and the default compression ratio, the first adjustment coefficient being greater than or equal to 1.

[0162] In a possible implementation, the determination module 13 is specifically configured to:

[0163] The first adjustment coefficient is greater than or equal to 1 and less than or equal to 2.

[0164] In a possible implementation, the determination module 13 is specifically configured to:

[0165] If the first set compression ratio is less than or equal to the first actual compression ratio, the second set compression ratio is determined as a product of a second adjustment coefficient and the default compression ratio, the second adjustment coefficient being less than or equal to 1.

[0166] If the first set compression ratio is greater than the first actual compression ratio, the second set compression ratio is determined as the default compression ratio.

[0167] In a possible implementation, the determining module 13 is specifically configured to:

[0168] The second adjustment coefficient is greater than or equal to 0.5 and less than or equal to 1.

[0169] In a possible implementation, the second obtaining module 12 is specifically configured to:

[0170] Obtain the gray value of each pixel in the second image.

[0171] Determine the variance value corresponding to the second image according to the gray value of each pixel in the second image.

[0172] Determine the content complexity of the second image according to the variance value corresponding to the second image.

[0173] In a possible implementation, the compressing module 14 is specifically configured to:

[0174] Obtain the first image that has been compressed in the DDR display memory.

[0175] Decompress the first image.

[0176] Perform three-dimensional noise reduction processing on the second image through the first image after decompression processing, to obtain the second image after noise reduction processing.

[0177] Compress the second image after noise reduction processing through the second set compression ratio.

[0178] Figure 7 Another structural schematic diagram of the image processing apparatus provided by the embodiments of the present application is provided. Please refer to Figure 7 The image processing apparatus 10 further includes a storage module 15:

[0179] The storage module 15 is configured to store the second image after compression processing to the DDR display memory.

[0180] The image processing apparatus provided by the embodiments of the present application can execute the technical solutions shown in the method embodiments, and the implementation principles and beneficial effects are similar, which will not be repeated here.

[0181] Figure 8A hardware structure schematic diagram of an image processing device provided by the embodiment of the present application is shown in FIG. 1. Please refer to FIG. 1. Figure 8 The image processing device 20 can include a processor 21 and a memory 22. The processor 21 and the memory 22 can communicate with each other. For example, the processor 21 and the memory 22 can communicate with each other through a communication bus 23.

[0182] The memory 22 is configured to store computer-executable instructions.

[0183] The processor 21 is configured to execute the computer-executable instructions stored in the memory 22, so that the processor 21 performs the image processing method shown in the above method embodiments.

[0184] Optionally, the image processing device 20 can further include a communication interface, which can include a transmitter and / or a receiver.

[0185] Optionally, the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0186] The embodiment of the present application provides a readable storage medium, and the readable storage medium stores a computer program. The computer program is used to implement the image processing method in any of the above embodiments.

[0187] The embodiment of the present application provides a computer program product, and the computer program product includes instructions. When the instructions are executed, the computer executes the image processing method.

[0188] All or part of the steps of the above method embodiments can be completed by program instruction related hardware. The foregoing program can be stored in a readable memory. When the program is executed, the steps of the above method embodiments are executed. The foregoing memory (storage medium) includes a read-only memory (English: read-only memory, abbreviation: ROM), RAM, flash memory, hard disk, solid state disk, magnetic tape, floppy disk, optical disc, and any combination thereof.

[0189] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as a combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices generate a device that implements the flowcharts and / or block diagrams. Figure 1 one flow or a plurality of flows and / or blocks Figure 1 an apparatus that implements the functions specified in one block or a plurality of blocks.

[0190] It can be understood that the various numerical numbers involved in the embodiments of the present application are only for the convenience of differentiation, and do not limit the scope of the embodiments of the present application.

[0191] In the present application, the term "comprising" and its variants can refer to non-limiting inclusion; the term "or" and its variants can refer to "and / or". In the present application, the terms "first", "second", etc. are used to distinguish similar objects, and do not necessarily refer to a specific order or sequence. In the present application, "a plurality of" refers to two or more. "And / or", which describes the relationship between the associated objects, means that there can be three relationships, for example, A and / or B can represent the three cases of A alone, A and B together, and B alone. The character " / " generally represents that the associated objects before and after are in an "or" relationship.

[0192] Obviously, those skilled in the art can make various modifications and variations to the embodiments of the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. An image processing method, characterized by, The method comprises the following steps: obtaining a first set compression ratio and a first actual compression ratio of a first image; obtaining a content complexity of a second image, the second image being a next frame image of the first image; if the content complexity is greater than a first threshold value and less than a second threshold value, determining a second actual compression ratio as a default compression ratio, the second threshold value being greater than the first threshold value; if the content complexity is less than or equal to the first threshold value, or the content complexity is greater than or equal to the second threshold value, determining the second actual compression ratio of the second image according to the first set compression ratio and the first actual compression ratio; compressing the second image according to the second actual compression ratio.

2. The method of claim 1, wherein, The content complexity is less than or equal to the first threshold value. The step of determining the second actual compression ratio according to the first set compression ratio and the first actual compression ratio comprises the following steps: if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second actual compression ratio as the default compression ratio; if the first set compression ratio is greater than the first actual compression ratio, determining the second actual compression ratio as a product of a first adjustment coefficient and the default compression ratio, the first adjustment coefficient being greater than or equal to 1.

3. The method of claim 2, wherein, The first adjustment coefficient is greater than or equal to 1 and less than or equal to 2.

4. The method of claim 1, wherein, The content complexity is greater than or equal to the second threshold value. The step of determining the second actual compression ratio according to the first set compression ratio and the first actual compression ratio comprises the following steps: if the first set compression ratio is less than or equal to the first actual compression ratio, determining the second actual compression ratio as a product of a second adjustment coefficient and the default compression ratio, the second adjustment coefficient being less than or equal to 1; if the first set compression ratio is greater than the first actual compression ratio, determining the second actual compression ratio as the default compression ratio.

5. The method of claim 4, wherein, The second adjustment coefficient is greater than or equal to 0.5 and less than or equal to 1.

6. The method according to any one of claims 1 to 5, characterized in that, The step of obtaining the content complexity of the second image comprises the following steps: obtaining a gray value of each pixel in the second image; determining a variance value corresponding to the second image according to the gray value of each pixel in the second image; determining the content complexity of the second image according to the variance value corresponding to the second image.

7. The method according to any one of claims 1 to 5, characterized in that, The step of compressing the second image according to the second actual compression ratio comprises the following steps: obtaining the first image having been compressed in a double data rate (DDR) memory; decompressing the first image; performing three-dimensional noise reduction processing on the second image through the decompressed first image to obtain a second image having been subjected to noise reduction processing; compressing the second image having been subjected to noise reduction processing according to the second actual compression ratio.

8. The method according to any one of claims 1 to 5, characterized in that, After the step of compressing the second image according to the second actual compression ratio, the method further comprises the following step: storing the second image having been compressed to the DDR memory.

9. An image processing apparatus characterized by comprising: The device comprises a first obtaining module, a second obtaining module, a determining module and a compressing module, wherein: the first obtaining module is configured to obtain a first set compression ratio and a first actual compression ratio of a first image; The second obtaining module is configured to obtain a content complexity of a second image, the second image being a next frame image of the first image; The determining module is configured to determine that a second actual compression ratio is a default compression ratio if the content complexity is greater than a first threshold value and less than a second threshold value, the second threshold value being greater than the first threshold value; If the content complexity is less than or equal to the first threshold value or the content complexity is greater than or equal to the second threshold value, a second actual compression ratio of the second image is determined according to the first set compression ratio and the first actual compression ratio; The compression module is configured to perform compression processing on the second image according to the second actual compression ratio.

10. An image processing apparatus characterized by comprising: Comprise: a processor and a memory; The memory is configured to store a computer program; The processor is configured to execute the computer program stored in the memory to implement the method in any one of claims 1 to 8.

11. A computer readable storage medium, characterized in that, In which, The computer readable storage medium stores computer execution instructions, when the computer execution instructions are executed by the processor, are configured to implement the method in any one of claims 1 to 8.

12. A computer program product, characterised in that, Comprise a computer program, when the computer program is executed by the processor, implement the method in any one of claims 1 to 8.

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