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

Abstract

The present disclosure provides a video processing method and apparatus, a device, a storage medium, and a program product. The method comprises: acquiring video data; performing data conversion on the 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 second components of the plurality of 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; on the basis of the target component and the color difference component, obtaining a target video frame corresponding to the current video frame; and obtaining a target video on the basis of the target video frame.

Description

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

[0001] This application claims priority to the Chinese invention patent application entitled “Video processing method, device, equipment, medium and program product” and application number 202311024765.4, filed on August 14, 2023. The entire contents of that application are incorporated by reference into this application. Technical Field

[0002] The present disclosure relates to the field of computer technology, and in particular to a video processing method, apparatus, device, medium, and program product. Background Art

[0003] Video data often contains a lot of image noise, which can make the video data unclear, affect the video presentation, and reduce the user's viewing experience. Video noise reduction can reduce image noise to a certain extent, but the noise reduction results still suffer from inter-frame jitter and consume a lot of computing and storage resources, resulting in poor noise reduction results and low efficiency.

[0004] Summary of the Invention

[0005] The present disclosure provides a video processing method, apparatus, device, 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.

[0006] In a first aspect of the present disclosure, a video processing method is provided, comprising: acquiring video data; performing data conversion on a 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 multiple second components of the adjacent video frames; performing noise reduction processing on the first component and the multiple 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.

[0007] In a second aspect of the present disclosure, a video processing device is provided, comprising: an acquisition module for acquiring video data; a data conversion module for performing data conversion on a 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 multiple second components of the adjacent video frames; a noise reduction module for performing noise reduction processing on the first component and the multiple second components to obtain a target component of the current video frame; 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; and a synthesis module for obtaining a target video based on the target video frame.

[0008] In 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 programs include instructions for executing the method according to the first aspect or the second aspect.

[0009] 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.

[0010] 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. 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 any creative work.

[0012] FIG1 is a schematic diagram of a video processing architecture according to an embodiment of the present disclosure.

[0013] FIG2 is a schematic diagram of the hardware structure of an exemplary electronic device according to an embodiment of the present disclosure.

[0014] FIG3 is a schematic flowchart of a video processing method according to an embodiment of the present disclosure.

[0015] FIG4 is a schematic diagram of a video processing method according to an embodiment of the present disclosure.

[0016] FIG5 is a schematic diagram of a video processing device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] 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 conjunction with specific embodiments and with reference to the accompanying drawings.

[0018] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the usual meanings 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. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include 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 may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the described object changes, the relative position relationship may also change accordingly.

[0019] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this 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.

[0020] For example, in response to a user's active request, a prompt message is sent to the user to clearly inform the user that the operation requested will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the electronic device, application, server, storage medium, or other software or hardware that performs the operations of the disclosed technical solution based on the prompt message.

[0021] As an optional but non-limiting implementation, in response to receiving a user's active request, 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. Furthermore, the pop-up window may also contain a selection control for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0022] It is understandable that the above notification and user authorization process are merely illustrative and do not limit the implementation of the present disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0023] FIG1 shows a schematic diagram of a video processing architecture according to an embodiment of the present disclosure. Referring to FIG1 , the video processing architecture 100 may include a server 110, a terminal 120, and a network 130 providing 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, a server cluster or a 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.

[0024] Terminal 120 can be implemented in hardware or software. For example, when implemented in hardware, terminal 120 can be any electronic device with a display screen that supports page display, including but not limited to smartphones, tablet computers, e-book readers, laptop computers, and desktop computers. When terminal 120 is implemented in software, it can be installed in the electronic devices listed above; it can be implemented as multiple software or software modules (such as software or software modules used to provide distributed services), or it can be implemented as a single software or software module, and no specific limitations are given here.

[0025] It should be noted that the video processing method provided in the embodiments of the present application can be executed by the terminal 120 or by the server 110. It should be understood that the number of terminals, networks, and servers in FIG1 is for illustration only and is not intended to limit the number thereof. Any number of terminals, networks, and servers can be used as required.

[0026] Figure 2 shows a schematic diagram of the hardware structure of an exemplary electronic device 200 provided by an embodiment of the present disclosure. As shown in Figure 2, 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, memory 204, network module 206, and peripheral interface 208 are communicatively connected to each other within electronic device 200 via bus 210.

[0027] The processor 202 may be a central processing unit (CPU), a video processor, a neural network processor (NPU), a microcontroller (MCU), a programmable logic device (PLD), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or one or more integrated circuits. The processor 202 may be configured to perform functions related to the technology described in this disclosure. In some embodiments, the processor 202 may also include multiple processors integrated into a single logical component. For example, as shown in FIG2 , the processor 202 may include multiple processors 202 a, 202 b, and 202 c.

[0028] The memory 204 can be configured to store data (e.g., instructions, computer codes, etc.). As shown in Figure 2, the data stored in the memory 204 can 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 can store configuration files of other modules, etc.). The processor 202 can 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 can include a volatile storage device or a non-volatile storage device. In some embodiments, the memory 204 can 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.

[0029] The network module 206 can be configured to provide the electronic device 200 with communication with other external devices 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)), a cellular network, the Internet, or a combination thereof. It will be appreciated that the type of network is not limited to the specific examples above. 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, and the like.

[0030] The peripheral interface 208 can be configured to connect the electronic device 200 to one or more peripheral devices to implement information input and output. For example, the peripheral devices can include input devices such as a keyboard, a mouse, a touchpad, a touch screen, a microphone, and various sensors, and output devices such as a display, a speaker, a vibrator, and an indicator light.

[0031] The bus 210 can be configured to transmit information between the 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.

[0032] It should be noted that although the architecture of the electronic device 200 shown above only includes the processor 202, the memory 204, the network module 206, the peripheral interface 208, and the bus 210, in a specific implementation, the architecture of the electronic device 200 may also include other components necessary for normal operation. In addition, those skilled in the art will understand that the architecture of the electronic device 200 may also include only the components necessary to implement the embodiments of the present disclosure, and does not necessarily include all the components shown in the figure.

[0033] 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, 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 performing denoising fusion on them together. The more video frames there are, the better the denoising effect, but the amount of calculation will also increase, and the processing efficiency will decrease. Therefore, how to balance improving the effect and efficiency of video denoising processing has become a technical problem that needs to be solved urgently.

[0034] In view of this, embodiments of the present disclosure provide a video processing method, apparatus, device, storage medium, and program product. This method performs noise reduction and fusion on the image components of multiple consecutive video frames in video data to obtain a target component, combines this with the original color difference component to obtain a target video frame, and then produces a denoised target video. This method ensures the consistency of the video frames after noise reduction processing, avoids inter-frame jitter, and improves the noise reduction effect of the video data. It also reduces the use of computing and storage resources and improves the efficiency of the noise reduction process.

[0035] Specifically, the video data may include a sequence of video frames, each of which may have color channel information (e.g., RGB channel information). Based on the analysis of image noise in the present application, it is determined that image noise mainly appears in the brightness component of the video frame (e.g., Y channel information in the YUV color space). Based on this, it is possible to perform noise reduction processing on only the brightness component to ensure the noise reduction effect, while also reducing the occupation of computing resources and storage resources and improving the efficiency of the noise reduction processing. Then, the video data can be converted to an image format (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 are subjected to noise reduction fusion to obtain a target brightness component after noise reduction processing. The target brightness component is then combined with the original color difference component of the video frame and the inverse transformation of the image format conversion (e.g., from YUV format to RGB format) is performed to obtain the target video frame after noise reduction processing for each video frame. Finally, the target video after noise reduction processing is synthesized based on all the target video frames.

[0036] 3 , which shows a schematic flow chart of a video processing method according to an embodiment of the present disclosure. The video processing method according to an embodiment of the present disclosure can be deployed on a client. In FIG3 , the video processing method 300 can further include the following steps.

[0037] In step S310, video data is acquired.

[0038] In some embodiments, each video frame in the video data may have corresponding RGB channel information. Referring to FIG4 , FIG4 shows a schematic diagram of a video processing method according to an embodiment of the present disclosure. As shown in FIG4 , the video data to be processed 410 may include multiple consecutive video frames 411 .

[0039] 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 the first component and color difference component of the current video frame and the second components of multiple adjacent video frames.

[0040] In some embodiments, the plurality of adjacent video frames may refer to several video frames adjacent to the current video frame. It should be understood that the plurality of adjacent video frames may be adjacent to the current video frame as a whole and are not intended to be limited to the frames before and after the current video frame.

[0041] In some embodiments, the plurality of adjacent video frames include: a first number of video frames preceding the current video frame, and / or a second number of video frames following the current video frame. Specifically, the plurality of adjacent video frames may be located only before the current video frame, such as adjacent video frames F1-F2 in FIG. 4 ; may be located only after the current video frame, such as adjacent video frames F4-F5 in FIG. 4 ; or may include both video frames preceding and following the current video frame F3, such as adjacent video frames F1-F2 and F4-F5 in FIG. 4 .

[0042] Furthermore, in some embodiments, the first number and the second number may be the same or different. For example, as shown in FIG4 , the first number and the second number may be the same, both 2, in which case 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 may 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-mentioned first number and second number are merely examples and are not intended to be limiting. The first number and second number may be set as needed.

[0043] 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.

[0044] In some embodiments, data conversion is performed on a current video frame in the video data and multiple adjacent video frames of the current video frame to obtain a first component and a color difference component of the current video frame and second components of multiple adjacent video frames, including: converting the current video frame and the adjacent video frames from RGB format to YUV format to obtain YUV channel information of the current video frame and Y channel information of the adjacent video frames; determining the Y channel information of the current video frame as the first component, and the U channel information and V channel information as the color difference component; and determining the Y channel information of the adjacent video frames as the second component.

[0045] In some embodiments, the first component and the second component may refer to a brightness component or an intensity component. Specifically, as shown in FIG4 , the current video frame F3 and its adjacent video frames F1-F2 and F4-F5 may be converted into an image format, and these video frames F1-F5 may be converted from RGB format to YUV format to obtain 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 the V channel information V3 of the current video frame F3; the second brightness component is the Y channel information Y1-Y2 and Y4-Y5 of the adjacent video frames F1-F2 and F4-F5.

[0046] In step S330, noise reduction processing is performed on the first component and the plurality of second components to obtain a target component of the current video frame.

[0047] In some embodiments, the first component and multiple second components are subjected to noise reduction processing to obtain the target component of the current video frame, including: splicing the first component and multiple second components to obtain a component sequence; performing feature extraction on the component sequence to obtain a feature sequence; and performing noise reduction processing based on the feature sequence to obtain the target component.

[0048] Specifically, referring to 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 extracts features from 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 traditional solution, 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 it is impossible to strike a balance between denoising effect and efficiency. Compared with traditional solutions, the video processing method of the embodiment of the present disclosure performs noise reduction processing and fusion for each video frame based only on the Y channel information of the video frame and its multiple adjacent video frames. This can not only ensure the noise reduction effect, but also reduce the memory usage 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.

[0049] In some embodiments, an initial neural network can be trained based on training data to obtain a trained denoising network 430. Specifically, the training data can 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 sequences of the multiple training image frames can be used as input layer data of the initial neural network, and the corresponding denoised training image frames can be used as output layer data of the initial neural network. The initial neural network can be trained to obtain a trained denoising network.

[0050] In some embodiments, performing noise reduction processing based on the feature 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; and obtaining the target component based on the target component features.

[0051] In some embodiments, the features in the feature sequence may be fused first and then subjected to noise reduction processing to obtain the target component.

[0052] In some embodiments, noise reduction processing is performed based on the brightness feature sequence to obtain the target brightness component, including: performing noise reduction processing on the features in the feature sequence to obtain a noise reduction feature sequence; performing feature fusion on the noise reduction feature sequence to obtain a target noise reduction feature; and obtaining the target component based on the target noise reduction feature.

[0053] In some embodiments, the features in the feature sequence may be subjected to noise reduction processing before being fused to obtain the target component.

[0054] 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.

[0055] In some embodiments, the target component of the current video frame after noise reduction processing can be combined with the original color difference component of the current video frame to obtain the noise reduction result of the current video frame. For example, as shown in Figure 4, the target luminance component 440 and the color difference components U3 and V3 of the current video frame F3 can be used to obtain the noise reduction result corresponding to the current video frame F3.

[0056] 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: converting the target component and the color difference component in YUV format into RGB components in RGB format; and obtaining the target video frame based on the RGB components.

[0057] Specifically, the target component 440 and the color difference components U3 and V3 are converted from the YUV format to the RGB format, so as to obtain a target video frame having RGB components corresponding to the current video frame, as shown in the target video frame FO in FIG. 4 .

[0058] In step S350, a target video is obtained based on the target video frame.

[0059] Specifically, as shown in FIG4 , 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.

[0060] It should be noted that the method of the embodiments of the present disclosure can be performed by a single device, such as a computer or server. The method of the embodiments of the present disclosure can also be applied in a distributed scenario, where multiple devices cooperate to perform the method. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiments of the present disclosure, and the multiple devices will interact with each other to complete the method.

[0061] It should be noted that the above description is limited to some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] Based on the same technical concept, corresponding to any of the above embodiments and methods, the present disclosure further provides a video processing device, as shown in FIG5 , comprising:

[0063] The acquisition module is used to obtain video data.

[0064] The data conversion module is used to perform data conversion on the current video frame and multiple adjacent video frames of the current video frame in the video data to obtain the first component and color difference component of the current video frame and the second components of multiple adjacent video frames.

[0065] The noise reduction module is configured to perform noise reduction processing on the first component and the plurality of second components to obtain a target component of the current video frame.

[0066] The data conversion module is further configured to obtain a target video frame corresponding to the current video frame based on the target component and the color difference component.

[0067] A synthesis module is used to obtain a target video based on the target video frame.

[0068] For the convenience of description, the above devices are described as being functionally divided into various modules. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0069] The apparatus 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.

[0070] 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, which 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.

[0071] The computer-readable media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules 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 disc read-only memory (CD-ROM), digital versatile disc (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.

[0072] The computer instructions stored in the storage medium of the above embodiment 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.

[0073] As can be seen from the foregoing, the video processing method, apparatus, device, medium, and program product provided herein are based on performing noise reduction and fusion on the image components of multiple consecutive video frames in video data to obtain a target component, which is then combined with the original color difference component to obtain a target video frame, thereby obtaining a noise-reduced target video. This method ensures the consistency of the video frames after noise reduction processing, avoids inter-frame jitter, and improves the noise reduction effect of the video data. It also reduces the use of computing and storage resources and improves the efficiency of the noise reduction process.

[0074] 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. Within the scope 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.

[0075] In addition, to simplify the description and discussion, and so as not to obscure the embodiments of the present disclosure, known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, devices may be shown in the form of block diagrams to avoid obscuring the embodiments of the present disclosure, 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 are to be implemented (i.e., these details should be fully within the purview of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure may be implemented without these specific details or with variations in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0076] Although the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0077] 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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