Video processing method and device, equipment, medium and program product

Abstract

The invention provides a video processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring video data; performing data conversion on a current video frame in the video data and a plurality of adjacent video frames of the current video frame to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames; performing noise reduction processing on the first component and the plurality of second components to obtain a target component of the current video frame; obtaining a target video frame corresponding to the current video frame based on the target component and the color difference component; and obtaining a target video based on the target video frame.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a video processing method, device, equipment, medium and program product. Background Art

[0002] There is often a lot of image noise in video data, which will make the video data unclear, affect the presentation of the video data, and reduce the user's viewing experience. Video noise reduction processing can reduce image noise to a certain extent, but the noise reduction result still has the problem of inter-frame jitter, and at the same time, it occupies a lot of computing and storage resources, resulting in poor noise reduction effect and low efficiency. Summary of the invention

[0003] The present disclosure proposes a video processing method, device, equipment, storage medium and program product to solve the technical problems of poor effect and low efficiency of video noise reduction processing to a certain extent.

[0004] In a first aspect, the present disclosure provides a video processing method, comprising:

[0005] Get video data;

[0006] Performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames;

[0007] Performing noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame;

[0008] Obtaining a target video frame corresponding to the current video frame based on the target component and the color difference component;

[0009] A target video is obtained based on the target video frame.

[0010] In a second aspect of the present disclosure, a video processing device is provided, comprising:

[0011] An acquisition module, used for acquiring video data;

[0012] A data conversion module, used for performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames;

[0013] A noise reduction module, configured to perform noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame;

[0014] The data conversion module is further used to: obtain a target video frame corresponding to the current video frame based on the target component and the color difference component;

[0015] A synthesis module is used to obtain a target video based on the target video frame.

[0016] According to a third aspect of the present disclosure, an electronic device is provided, characterized in that it includes one or more processors, a memory; and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, and the program includes instructions for executing the method described in the first aspect or the second aspect.

[0017] According to a fourth aspect of the present disclosure, a non-volatile computer-readable storage medium containing a computer program is provided. When the computer program is executed by one or more processors, the processors execute the method described in the first aspect or the second aspect.

[0018] In a fifth aspect of the present disclosure, a computer program product is provided, comprising computer program instructions, which, when executed on a computer, cause the computer to execute the method described in the first aspect.

[0019] From the above, it can be seen that the video processing method, device, equipment, medium and program product provided by the present disclosure are based on the noise reduction fusion of the image components of multiple consecutive video frames in the video data to obtain the target component, combined with the original color difference component to obtain the target video frame, and then obtain the target video after noise reduction. It can ensure the consistency of the video frame after the video data noise reduction processing, avoid inter-frame jitter, and improve the noise reduction effect of the video data; at the same time, it also reduces the occupation of computing resources and storage resources, and improves the efficiency of noise reduction processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of a video processing architecture according to an embodiment of the present disclosure.

[0022] Figure 2 The figure is a schematic diagram of the hardware structure of an exemplary electronic device according to an embodiment of the present disclosure.

[0023] Figure 3 The figure is a schematic flow chart of a video processing method according to an embodiment of the present disclosure.

[0024] Figure 4 Schematic diagram of a video processing method according to an embodiment of the present disclosure.

[0025] Figure 5 Schematic diagram of a video processing device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0027] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0028] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0029] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0030] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0031] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0032] Figure 1 FIG. 1 is a schematic diagram showing a video processing architecture of an embodiment of the present disclosure. Figure 1 The video processing architecture 100 may include a server 110, a terminal 120, and a network 130 that provides a communication link. The server 110 and the terminal 120 may be connected via a wired or wireless network 130. The server 110 may be an independent physical server, or a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, security services, and CDN.

[0033] The terminal 120 may be implemented in hardware or software. For example, when the terminal 120 is implemented in hardware, it may be various electronic devices having a display screen and supporting page display, including but not limited to smart phones, tablet computers, e-book readers, laptop portable computers, and desktop computers, etc. When the terminal 120 device is implemented in software, it may be installed in the electronic devices listed above; it may be implemented as multiple software or software modules (such as software or software modules used to provide distributed services), or it may be implemented as a single software or software module, which is not specifically limited here.

[0034] It should be noted that the video processing method provided in the embodiment of the present application can be executed by the terminal 120 or by the server 110. It should be understood that Figure 1 The number of terminals, networks and servers in the embodiment is only for illustration and is not intended to limit the number of terminals, networks and servers. Any number of terminals, networks and servers may be provided as required.

[0035] Figure 2 FIG. 2 shows a schematic diagram of the hardware structure of an exemplary electronic device 200 provided in an embodiment of the present disclosure. Figure 2 As shown, the electronic device 200 may include: a processor 202, a memory 204, a network module 206, a peripheral interface 208 and a bus 210. The processor 202, the memory 204, the network module 206 and the peripheral interface 208 are connected to each other in communication within the electronic device 200 through the bus 210.

[0036] Processor 202 may be a central processing unit (CPU), a video processor, a neural network processor (NPU), a microcontroller (MCU), a programmable logic device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), or one or more integrated circuits. Processor 202 may be used to perform functions related to the technology described in this disclosure. In some embodiments, processor 202 may also include multiple processors integrated into a single logical component. For example, Figure 2 As shown, processor 202 may include a plurality of processors 202a, 202b, and 202c.

[0037] The memory 204 may be configured to store data (eg, instructions, computer code, etc.). Figure 2 As shown, the data stored in the memory 204 may include program instructions (e.g., program instructions for implementing the video processing method of the embodiment of the present disclosure) and data to be processed (e.g., the memory may store configuration files of other modules, etc.). The processor 202 may also access the program instructions and data stored in the memory 204, and execute the program instructions to operate on the data to be processed. The memory 204 may include a volatile storage device or a non-volatile storage device. In some embodiments, the memory 204 may include a random access memory (RAM), a read-only memory (ROM), an optical disk, a magnetic disk, a hard disk, a solid-state drive (SSD), a flash memory, a memory stick, etc.

[0038] The network module 206 can be configured to provide communication with other external devices to the electronic device 200 via a network. The network can be any wired or wireless network capable of transmitting and receiving data. For example, the network can be a wired network, a local wireless network (e.g., Bluetooth, WiFi, near field communication (NFC) etc.), a cellular network, the Internet or a combination thereof. It is understood that the type of network is not limited to the above specific examples. In some embodiments, the network module 306 can include any number of network interface controllers (NICs), radio frequency modules, transceivers, modems, routers, gateways, adapters, cellular network chips, etc., in any combination.

[0039] The peripheral interface 208 can be configured to connect the electronic device 200 to one or more peripheral devices to achieve information input and output. For example, the peripheral devices can include input devices such as a keyboard, a mouse, a touch pad, a touch screen, a microphone, and various sensors, and output devices such as a display, a speaker, a vibrator, and an indicator light.

[0040] The bus 210 can be configured to transmit information between various components of the electronic device 200 (e.g., the processor 202, the memory 204, the network module 206, and the peripheral interface 208), such as an internal bus (e.g., a processor-memory bus), an external bus (USB port, PCI-E bus), etc.

[0041] It should be noted that, although the architecture of the electronic device 200 only shows the processor 202, the memory 204, the network module 206, the peripheral interface 208 and the bus 210, in the specific implementation process, the architecture of the electronic device 200 may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the architecture of the electronic device 200 may also only include the components necessary for implementing the embodiments of the present disclosure, and does not necessarily include all the components shown in the figure.

[0042] Compared with image denoising, video denoising not only focuses on the denoising effect of each video frame, but also needs to pay attention to the consistency between video frames to prevent jitter between video frames. However, the existing video denoising processing methods usually perform denoising fusion based on the RGB channel information of multiple video frames to obtain denoised video data. Since the amount of RGB channel information data of multiple video frames is large, a large amount of storage and computing resources will be occupied when they are denoised together. The more the number of the multiple video frames, the better the denoising effect, but the amount of calculation also increases, and the processing efficiency becomes lower. Therefore, how to balance improving the effect and efficiency of video denoising processing has become a technical problem that needs to be solved urgently.

[0043] In view of this, the embodiments of the present disclosure provide a video processing method, apparatus, device, storage medium and program product. Based on the noise reduction fusion of the image components of multiple consecutive video frames in the video data, the target component is obtained, and the target video frame is obtained by combining the original color difference component, and then the target video after noise reduction is obtained. The consistency of the video frame after the video data noise reduction processing can be ensured, the jitter between frames can be avoided, and the noise reduction effect of the video data can be improved; at the same time, the occupation of computing resources and storage resources is reduced, and the efficiency of noise reduction processing is improved.

[0044] Specifically, the video data may include a sequence of video frames, wherein each video frame may have color channel information (e.g., RGB channel information). Based on the analysis of the image noise in the present application, it is determined that the image noise mainly appears in the brightness component of the video frame (e.g., the Y channel information in the YUV color space). Accordingly, only the brightness component can be subjected to noise reduction processing to ensure the noise reduction effect, and at the same time, the occupation of computing resources and storage resources can be reduced, thereby improving the efficiency of the noise reduction processing. Then, the video data may be subjected to image format conversion Transfer (e.g., from RGB format to YUV format) to obtain the brightness component and color difference component of each video frame in the video data (e.g., U channel information and Y channel information in the YUV color space). For each video frame, the brightness component of the video frame and its multiple adjacent video frames is subjected to noise reduction fusion to obtain the target brightness component after noise reduction processing. Based on the target brightness component, the original color difference component of the video frame is combined, and the inverse transformation of the image format conversion Transfer is performed (e.g., from YUV format to RGB format), the target video frame after noise reduction processing of each video frame is obtained. Finally, the target video subjected to noise reduction processing is synthesized based on all the target video frames.

[0045] See also Figure 3 , Figure 3 The schematic flow chart of the video processing method according to the embodiment of the present disclosure is shown. The video processing method according to the embodiment of the present disclosure can be deployed on the client. Figure 3 In the example, the video processing method 300 may further include the following steps.

[0046] In step S310, video data is acquired.

[0047] Each video frame in the video data may have corresponding RGB channel information. Figure 4 , Figure 4 FIG. 1 is a schematic diagram showing a video processing method according to an embodiment of the present disclosure. Figure 4 As shown, the video data 410 to be processed may include a plurality of consecutive video frames 411 .

[0048] In step S320, data conversion is performed on the current video frame and multiple adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and second components of multiple adjacent video frames.

[0049] The multiple adjacent video frames may refer to several video frames adjacent to the current video frame. It should be understood that the multiple adjacent video frames may be adjacent to the current video frame as a whole, and are not intended to be limited to the previous and next frames of the current video frame.

[0050] In some embodiments, the plurality of adjacent video frames include: a first number of video frames located before the current video frame, and / or a second number of video frames located after the current video frame. Specifically, the plurality of adjacent video frames may only be located before the current video frame, for example Figure 4 The adjacent video frames F1-F2 in the video frame may also be located only after the current video frame, for example Figure 4 The adjacent video frames F4-F5 in the current video frame may also include the video frames before and after the current video frame F3, for example Figure 4 Adjacent video frames F1-F2, F4-F5 in .

[0051] Furthermore, in some embodiments, the first number and the second number may be the same or different. Figure 4 As shown, the first number and the second number can be the same, both 2, then the multiple adjacent video frames before the current video frame F3 are F1-F2, and the multiple adjacent video frames after the current video frame F3 are F4-F5. The first number and the second number can also be different. For example, when the first number is 2 and the second number is 1, the multiple adjacent video frames may include F1-F2 and F4. It should be understood that the above first number and second number are only examples and are not intended to limit them. The first number and the second number can be set as needed.

[0052] In some embodiments, the data conversion may include image format conversion. Further, the image format conversion may include conversion from RGB format to YUV format.

[0053] In some embodiments, performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames includes:

[0054] Convert the current video frame and the adjacent video frame from RGB format to YUV format to obtain YUV channel information of the current video frame and Y channel information of the adjacent video frame;

[0055] Determine the Y channel information of the current video frame as the first component, and the U channel information and the V channel information as the color difference component; and determine the Y channel information of the adjacent video frame as the second component.

[0056] The first component and the second component may refer to brightness components or intensity components. Figure 4As shown, the image format conversion can be performed on the current video frame F3 and its adjacent video frames F1-F2, F4-F5, and these video frames F1-F5 are converted from RGB format to YUV format to obtain the YUV channel information of each video frame F1-F5. Among them, the YUV channel information of the video frame Fi is Yi, Ui, Vi, i=1, 2, ..., 5. Then the first brightness component is the Y channel information Y3 of the current video frame F3, and the color difference information is the U channel information U3 and V channel information V3 of the current video frame F3; the second brightness component is the Y channel information Y1-Y2, Y4-Y5 of the adjacent video frames F1-F2, F4-F5.

[0057] In step S330, noise reduction processing is performed on the first component and the plurality of the second components to obtain a target component of the current video frame.

[0058] In some embodiments, performing noise reduction processing on the first component and the plurality of the second components to obtain the target component of the current video frame includes:

[0059] concatenating the first component and a plurality of the second components to obtain a component sequence;

[0060] Extracting features from the component sequence to obtain a feature sequence;

[0061] A noise reduction process is performed based on the characteristic sequence to obtain the target component.

[0062] Specifically, see Figure 4 , the first component Y3 and multiple second components Y1-Y2, Y4-Y5 can be spliced ​​to obtain a component sequence 420. In some embodiments, the component sequence 420 can be input into a trained denoising network 430 to output a corresponding target component 440. Specifically, the denoising network 430 performs feature extraction on the component sequence 420 to obtain a feature sequence; then the feature sequence is denoised and fused to output the target component 440 after denoising. In the prior art, for each video frame, the denoising result of each video frame is obtained by inputting the adjacent video frames into the denoising model. The denoising effect increases with the increase in the number of adjacent video frames, but the corresponding computational complexity and memory overhead also increase rapidly, which is not friendly to the deployed terminal devices, and the denoising effect and efficiency cannot be balanced. Compared with the prior art, the video processing method of the embodiment of the present disclosure performs noise reduction processing and fusion for each video frame only based on the Y channel information of the video frame and its multiple adjacent video frames, which can not only ensure the noise reduction effect, but also reduce the memory occupancy of the video processing process, reduce the amount of calculation, save storage resources and computing resources, improve the efficiency of noise reduction processing, and can simultaneously improve the effect and efficiency of noise reduction processing.

[0063] In some embodiments, the initial neural network can be trained based on the training data to obtain a trained denoising network 430. Specifically, the training data may include at least one training sample, each training sample including a Y channel information sequence of multiple training image frames, and denoised training image frames corresponding to the multiple training image frames. The Y channel information sequence of multiple training image frames can be used as the input layer data of the initial neural network, and the corresponding denoised training image frames can be used as the output layer data of the initial neural network. The initial neural network can be trained to obtain a trained denoising network.

[0064] In some embodiments, performing noise reduction processing based on the feature sequence to obtain the target component includes:

[0065] Performing feature fusion on the features in the feature sequence to obtain fused features;

[0066] Performing noise reduction processing on the fused features to obtain the target component features;

[0067] The target component is obtained based on the target component feature.

[0068] Among them, the features in the feature sequence can be fused first and then subjected to noise reduction processing to obtain the target component.

[0069] In some embodiments, performing noise reduction processing based on the brightness feature sequence to obtain the target brightness component includes:

[0070] Performing denoising on the features in the feature sequence to obtain a denoised feature sequence;

[0071] Performing feature fusion on the noise reduction feature sequence to obtain a target noise reduction feature;

[0072] The target component is obtained based on the target noise reduction feature.

[0073] Among them, the features in the feature sequence can be first subjected to denoising and then fused to obtain the target component.

[0074] In step S340, a target video frame corresponding to the current video frame is obtained based on the target component and the color difference component.

[0075] The target component after the noise reduction processing of the current video frame can be combined with the original color difference component of the current video frame to obtain the result of the noise reduction processing of the current video frame. Figure 4 As shown, the target brightness component 440 and the color difference components U3 and V3 of the current video frame F3 can obtain the noise reduction processing result corresponding to the current video frame F3.

[0076] In some embodiments, obtaining a target video frame corresponding to the current video frame based on the target component and the color difference component includes:

[0077] Convert the target component and the color difference component in YUV format into RGB components in RGB format;

[0078] The target video frame is obtained based on the RGB components.

[0079] Specifically, the target component 440 and the color difference components U3 and V3 are converted from the YUV format to the RGB format, and the target video frame with RGB components corresponding to the current video frame can be obtained, such as Figure 4 The target video frame FO is shown in FIG.

[0080] In step S350, a target video is obtained based on the target video frame.

[0081] Specifically, Figure 4 As shown, the target video frame FO obtained from each video frame in the video data 410 is synthesized to obtain the target video 450 after noise reduction processing.

[0082] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0083] It should be noted that some embodiments of the present disclosure are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0084] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present disclosure also provides a video processing device, see Figure 5 , the video processing device comprises:

[0085] An acquisition module, used for acquiring video data;

[0086] A data conversion module, used for performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames;

[0087] A noise reduction module, configured to perform noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame;

[0088] The data conversion module is further used to: obtain a target video frame corresponding to the current video frame based on the target component and the color difference component;

[0089] A synthesis module is used to obtain a target video based on the target video frame.

[0090] For the convenience of description, the above device is described by dividing it into various modules according to its functions. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0091] The device of the above embodiment is used to implement the corresponding video processing method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0092] Based on the same technical concept, corresponding to any of the above-mentioned embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the video processing method described in any of the above embodiments.

[0093] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0094] The computer instructions stored in the storage medium of the above embodiments are used to enable the computer to execute the video processing method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0095] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples. Based on the concept of the present disclosure, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of simplicity.

[0096] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present disclosure difficult to understand, the known power / ground connections to the integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure will be implemented (that is, these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it is apparent to those skilled in the art that the embodiments of the present disclosure can be implemented without these specific details or with changes in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0097] Although the present disclosure has been described in conjunction with specific embodiments of the present disclosure, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0098] The embodiments of the present disclosure are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A video processing method, comprising: Get video data; Performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames; Performing noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame; Obtaining a target video frame corresponding to the current video frame based on the target component and the color difference component; A target video is obtained based on the target video frame.

2. The method according to claim 1, wherein Performing noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame includes: concatenating the first component and a plurality of the second components to obtain a component sequence; Extracting features from the component sequence to obtain a feature sequence; A noise reduction process is performed based on the characteristic sequence to obtain the target component.

3. The method according to claim 2, wherein: Performing noise reduction processing based on the characteristic sequence to obtain the target component includes: Performing feature fusion on the features in the feature sequence to obtain fused features; Performing noise reduction processing on the fused features to obtain the target component features; Obtaining the target component based on the target component feature; or, Performing denoising on the features in the feature sequence to obtain a denoised feature sequence; Performing feature fusion on the reduced-degree feature sequence to obtain a target noise reduction feature; The target component is obtained based on the target noise reduction feature.

4. The method according to claim 1, wherein The multiple adjacent video frames include: a first number of video frames located before the current video frame, and / or a second number of video frames located after the current video frame; wherein the first number is the same as or different from the second number.

5. The method according to claim 1, wherein: The method comprises: performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames, including: Convert the current video frame and the adjacent video frame from RGB format to YUV format to obtain YUV channel information of the current video frame and Y channel information of the adjacent video frame; Determine the Y channel information of the current video frame as the first component, and the U channel information and the V channel information as the color difference component; and determine the Y channel information of the adjacent video frame as the second component.

6. The method according to claim 1, wherein: Obtaining a target video frame corresponding to the current video frame based on the target component and the color difference component, including: Convert the target component and the color difference component in YUV format into RGB components in RGB format; The target video frame is obtained based on the RGB components.

7. A video processing device, comprising: An acquisition module, used for acquiring video data; A data conversion module, used for performing data conversion on a current video frame and a plurality of adjacent video frames of the current video frame in the video data to obtain a first component and a color difference component of the current video frame and a plurality of second components of the adjacent video frames; A noise reduction module, configured to perform noise reduction processing on the first component and the plurality of the second components to obtain a target component of the current video frame; The format conversion module is further used to: obtain a target video frame corresponding to the current video frame based on the target component and the color difference component; A synthesis module is used to obtain a target video based on the target video frame.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the program.

9. A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, comprising computer program instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 6.

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