Video coding method and device, bit stream generation method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a video coding method and device, a bit stream generation method and device, electronic equipment, a storage medium and a program product. The video coding method comprises the following steps: carrying out time domain filtering on a current frame to obtain a time domain filtering frame; performing weighted summation on the original frame of the current frame and the time domain filtering frame to generate a loop filtering target frame applied to a loop filtering tool of the current frame; determining a filtering parameter of a loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and the loop filtering target frame; and coding the current frame based on the determined filtering parameter. According to the present disclosure, the overall coding efficiency of all frames (reference frames and subsequent frames) can be improved.

Description

Technical Field

[0001] The present disclosure generally relates to the field of video encoding technology, and more specifically, to a video encoding method, a bit stream generation method, an apparatus, an electronic device, a storage medium, and a program product. Background Art

[0002] Various electronic devices (e.g., digital televisions, laptop or desktop computers, tablet computers, digital cameras, digital recording devices, digital media players, video game consoles, smart phones, video teleconferencing devices, video streaming devices, etc.) support digital video. Electronic devices send and receive or otherwise transmit digital video data through a communication network, and / or store digital video data on a storage device. Due to the limited bandwidth capacity of the communication network and the limited storage resources of the storage device, before the video data is transmitted or stored, the video data can be compressed using a video codec according to one or more video codec standards. For example, video codec standards include general video codec (VVC), joint exploration test model (JEM), high efficiency video codec (HEVC / H.265), advanced video codec (AVC / H.264), moving picture expert group (MPEG) codec, etc. Video codecs generally use prediction methods (e.g., inter-frame prediction, intra-frame prediction, etc.) that utilize the inherent redundancy in video data. Video codecs are intended to compress video data into a form that uses a lower bit rate while avoiding or minimizing the degradation of video quality.

[0003] The VTM (Versatile Video Coding Test Model) encoder uses MCTF (Motion Compensated Temporal Filter) frames as the target frames for adaptive loop filtering (ALF) and SAO (Sample Adaptive Offset), and trains the filter parameters of ALF and SAO to transmit to the decoder. If the loop filtering tool at the encoder uses MCTF frames as the target frames, that is, the reconstructed frames are close to MCTF frames, the coding efficiency of subsequent frames will be improved because the MCTF filtering reference effect can be fully propagated to subsequent frames; but on the other hand, because the reconstructed frames need to calculate the distortion indicators such as PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) with the original frames, this will lead to a decrease in the coding efficiency of the reference frames. Therefore, directly using MCTF frames as the target frames for loop filtering cannot achieve the highest joint coding efficiency of all frames (reference frames and subsequent frames). Summary of the invention

[0004] An exemplary embodiment of the present disclosure is to provide a video encoding method, a bitstream generation method, an apparatus, an electronic device, a storage medium, and a program product, which can improve the overall encoding efficiency of all frames (reference frames and subsequent frames).

[0005] According to a first aspect of an embodiment of the present disclosure, a video encoding method is provided, comprising: performing time domain filtering on a current frame to obtain a time domain filtered frame; performing weighted summation on an original frame of the current frame and the time domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame; determining filtering parameters of the loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and the loop filtering target frame; and encoding the current frame based on the determined filtering parameters.

[0006] Optionally, the weight corresponding to the original frame is a first preset value, and the weight corresponding to the time-domain filtered frame is a second preset value.

[0007] Optionally, the weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on content features of the original frame.

[0008] Optionally, the content feature includes at least one of the following items: noise feature, pixel mean, pixel variance, pixel gradient, motion vector mean, motion vector variance, quantization parameter in rate allocation and rate distortion cost of transform coefficient after motion compensation.

[0009] Optionally, the weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on the difference between the original frame and the time-domain filtered frame.

[0010] Optionally, the weight corresponding to the original frame is positively correlated with the difference, and the weight corresponding to the time-domain filtered frame is negatively correlated with the difference.

[0011] Optionally, the step of weighted summing the original frame and the time-domain filtered frame of the current frame to generate a loop filtering target frame of the loop filtering tool applied to the current frame includes: weighted summing the original frame itself and the time-domain filtered frame itself to generate the loop filtering target frame; or, weighted summing the original frame after spatial filtering and the time-domain filtered frame after spatial filtering to generate the loop filtering target frame; or, weighted summing the original frame after spatial filtering and the time-domain filtered frame itself to generate the loop filtering target frame; or, weighted summing the original frame itself and the time-domain filtered frame after spatial filtering to generate the loop filtering target frame.

[0012] Optionally, the step of performing weighted summation on the original frame and the time domain filtered frame of the current frame to generate a loop filtering target frame of the loop filtering tool applied to the current frame includes: performing weighted summation on the original frame and the time domain filtered frame to generate a target frame of the adaptive loop filtering tool applied to the current frame and / or a target frame of the sample adaptive offset tool applied to the current frame.

[0013] Optionally, the step of determining the filtering parameters of the loop filtering tool applied to the current frame based on the reconstructed frame of the current frame and the target frame of the loop filtering tool applied to the current frame includes: determining the filtering parameters of the adaptive loop filtering tool applied to the current frame based on the reconstructed frame of the current frame and the target frame of the adaptive loop filtering tool applied to the current frame; and / or determining the filtering parameters of the sample adaptive offset tool applied to the current frame based on the reconstructed frame of the current frame and the target frame of the sample adaptive offset tool applied to the current frame.

[0014] According to a second aspect of an embodiment of the present disclosure, a video encoding device is provided, comprising: a time domain filtering unit, configured to perform time domain filtering on a current frame to obtain a time domain filtered frame; a target frame generating unit, configured to perform weighted summation on an original frame of the current frame and the time domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame; a parameter determining unit, configured to determine filtering parameters of the loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and the loop filtering target frame; and an encoding unit, configured to encode the current frame based on the determined filtering parameters.

[0015] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: at least one processor; and at least one memory storing computer executable instructions, wherein when the computer executable instructions are executed by the at least one processor, the at least one processor is prompted to execute the video encoding method as described above.

[0016] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute the video encoding method as described above.

[0017] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising computer instructions, which implement the video encoding method as described above when executed by at least one processor.

[0018] According to a sixth aspect of an embodiment of the present disclosure, a method for generating a bitstream is provided, comprising: generating a bitstream according to the video encoding method as described above.

[0019] According to a seventh aspect of an embodiment of the present disclosure, a computer program product is provided, having instructions for storing a bit stream, wherein the bit stream includes: video data generated according to the video encoding method as described above.

[0020] According to the video encoding method, bitstream generation method, device, electronic device, storage medium and program product of the exemplary embodiments of the present invention, weighted summation is performed on the original frame and the time domain filtered frame to generate a loop filtering target frame, which can comprehensively consider the encoding efficiency of the reference frame and the subsequent frame and improve the overall encoding performance.

[0021] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0023] Figure 1 is a block diagram illustrating an exemplary system for encoding and decoding video blocks according to some embodiments of the present disclosure;

[0024] Figure 2 is a block diagram illustrating an exemplary video encoder according to some embodiments of the present disclosure;

[0025] Figure 3 is a block diagram illustrating an exemplary video decoder according to some embodiments of the present disclosure;

[0026] Figure 4 A flowchart showing a video encoding method according to an exemplary embodiment of the present disclosure is shown;

[0027] Figure 5 A structural block diagram of a video encoding device according to an exemplary embodiment of the present disclosure is shown;

[0028] Figure 6 A structural block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown;

[0029] Figure 7 is a diagram illustrating a computing environment coupled with a user interface according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0030] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0032] It should be noted that the phrase "at least one of the items" in the present disclosure includes three types of parallel situations: "any one of the items", "a combination of any number of the items", and "all of the items". For example, "including at least one of A and B" includes the following three parallel situations: (1) including A; (2) including B; (3) including A and B. Another example is "executing at least one of step 1 and step 2" which means the following three parallel situations: (1) executing step 1; (2) executing step 2; (3) executing step 1 and step 2.

[0033] Figure 1 is a block diagram illustrating an exemplary system 10 for encoding and decoding video blocks in parallel according to some embodiments of the present disclosure. Figure 1 As shown in , system 10 includes a source device 12 that generates and encodes video data to be later decoded by a target device 14. Source device 12 and target device 14 may include any of a wide variety of electronic devices, including cloud servers, server computers, desktop or laptop computers, tablet computers, smart phones, set-top boxes, digital televisions, cameras, display devices, digital media players, video game consoles, video streaming devices, etc. In some implementations, source device 12 and target device 14 are equipped with wireless communication capabilities.

[0034] In some implementations, target device 14 may receive the encoded video data to be decoded via link 16. Link 16 may include any type of communication medium or device capable of moving the encoded video data from source device 12 to target device 14.

[0035] In some other embodiments, the encoded video data may be sent from the output interface 22 to the storage device 32. The encoded video data in the storage device 32 may then be accessed by the target device 14 via the input interface 28.

[0036] like Figure 1, source device 12 includes a video source 18, a video encoder 20, and an output interface 22. Video source 18 may include sources such as, or a combination of such sources: a video capture device (e.g., a camera), a video archive containing previously captured video, a video feed interface for receiving video from a video content provider, and / or a computer graphics system for generating computer graphics data as source video.

[0037] The captured, pre-captured, or computer-generated video may be encoded by video encoder 20. The encoded video data may be sent directly to target device 14 via output interface 22 of source device 12. The encoded video data may also (or alternatively) be stored on storage device 32 for later access by target device 14 or other devices for decoding and / or playback.

[0038] Target device 14 includes input interface 28, video decoder 30, and display device 34. Input interface 28 may include a receiver and / or a modem and receives encoded video data via link 16. The encoded video data transmitted via link 16 or provided on storage device 32 may include various syntax elements generated by video encoder 20 for use by video decoder 30 in decoding the video data. Such syntax elements may be included within the encoded video data sent over a communication medium, stored on a storage medium, or stored on a file server.

[0039] The video encoder 20 and the video decoder 30 can operate according to a proprietary standard or an industry standard (e.g., VVC, HEVC, Part 10 of MPEG-4, AVC) or an extension of such a standard. It should be understood that the present application is not limited to a specific video encoding / decoding standard and can be applied to other video encoding / decoding standards. It is generally believed that the video encoder 20 of the source device 12 can be configured to encode the video data according to any of these current standards or future standards. Similarly, it is also generally believed that the video decoder 30 of the target device 14 can be configured to decode the video data according to any of these current standards or future standards.

[0040] The video encoder 20 and the video decoder 30 may be implemented as any of a variety of suitable encoder and / or decoder circuits, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic devices, software, hardware, firmware, or any combination thereof. When partially implemented in software, the electronic device may store instructions for the software in a suitable non-transitory computer-readable medium, and use one or more processors to execute the instructions in the hardware to perform the video encoding / decoding operations disclosed in the present disclosure. Each of the video encoder 20 and the video decoder 30 may be included in one or more encoders or decoders, and either of the encoders or decoders may be integrated as part of a combined encoder / decoder (CODEC) in the corresponding device.

[0041] Figure 2 is a block diagram illustrating an exemplary video encoder 20 according to some embodiments described in the present application. The video encoder 20 can perform intra-frame prediction coding and inter-frame prediction coding on video blocks within a video frame. Intra-frame prediction coding relies on spatial prediction to reduce or remove spatial redundancy in video data within a given video frame or picture. Inter-frame prediction coding relies on temporal prediction to reduce or remove temporal redundancy in video data within adjacent video frames or pictures of a video sequence. It should be noted that in the field of video coding and decoding, the term "frame" can be used as a synonym for the term "image" or "picture".

[0042] like Figure 2As shown in , the video encoder 20 includes a video data memory 40, a prediction processing unit 41, a decoded picture buffer (DPB) 64, an adder 50, a transform processing unit 52, a quantization unit 54, and an entropy coding unit 56. The prediction processing unit 41 further includes a motion estimation unit 42, a motion compensation unit 44, a segmentation unit 45, an intra-frame prediction processing unit 46, and an intra-frame block copy (BC) unit 48. In some embodiments, the video encoder 20 also includes an inverse quantization unit 58, an inverse transform processing unit 60, and an adder 62 for video block reconstruction. A loop filter 63 such as a deblocking filter can be located between the adder 62 and the DPB 64 to filter the block boundary to remove the block effect from the reconstructed video. In addition to the deblocking filter, another loop filter (e.g., a sample adaptive offset (SAO) filter, a cross-component sample adaptive offset (CCSAO) filter, and / or an adaptive loop filter (ALF)) can also be used to filter the output of the adder 62. In some examples, the loop filter may be omitted, and the decoded video blocks may be provided directly by adder 62 to DPB 64. Video encoder 20 may take the form of a fixed or programmable hardware unit, or may be distributed among one or more of the illustrated fixed or programmable hardware units.

[0043] Video data memory 40 may store video data to be encoded by components of video encoder 20. Figure 1 Video source 18 is shown obtaining video data in video data memory 40. DPB 64 is a buffer that stores reference video data (eg, reference frames or pictures) for use by video encoder 20 in encoding the video data (eg, in intra or inter prediction coding modes).

[0044] like Figure 2 As shown in , after receiving the video data, the segmentation unit 45 within the prediction processing unit 41 segments the video data into video blocks. This segmentation may also include segmenting the video frame into strips, tiles (e.g., a set of video blocks), or other larger coding units (CUs) according to a predefined splitting structure associated with the video data, such as a quadtree (QT) structure. It should be noted that the terms "block" or "video block" used herein may be a portion of a frame or picture, in particular a rectangular (square or non-square) portion. With reference to, for example, HEVC and VVC, a block or video block may be or correspond to a coding tree unit (CTU), a CU, a prediction unit (PU), or a transform unit (TU) and / or may be or correspond to a corresponding block (e.g., a coding tree block (CTB), a coding block (CB), a prediction block (PB), or a transform block (TB)) and / or a sub-block.

[0045] The prediction processing unit 41 may select one of a plurality of feasible prediction coding modes for the current video block based on the error results (e.g., coding rate and distortion level), such as one of one or more inter-frame prediction coding modes in a plurality of intra-frame prediction coding modes. The prediction processing unit 41 may provide the resulting intra-frame prediction coding block or inter-frame prediction coding block to the adder 50 to generate a residual block, and to the adder 62 to reconstruct the coding block for subsequent use as part of a reference frame. The prediction processing unit 41 also provides syntax elements (e.g., motion vectors, intra-frame mode indicators, partition information, and other such syntax information) to the entropy coding unit 56.

[0046] To select an appropriate intra-prediction coding mode for the current video block, intra-prediction processing unit 46 within prediction processing unit 41 may perform intra-prediction coding of the current video block in relation to one or more neighboring blocks in the same frame as the current block to be encoded to provide spatial prediction. Motion estimation unit 42 and motion compensation unit 44 within prediction processing unit 41 may perform inter-prediction coding of the current video block in relation to one or more prediction blocks in one or more reference frames to provide temporal prediction. Video encoder 20 may perform multiple encoding passes, for example, to select an appropriate coding mode for each block of video data.

[0047] In some embodiments, motion estimation unit 42 determines an inter-prediction mode for a current video frame by generating a motion vector according to a predetermined pattern within a sequence of video frames, the motion vector indicating the displacement of a video block within the current video frame relative to a prediction block within a reference video frame. Motion estimation performed by motion estimation unit 42 is the process of generating a motion vector that estimates the motion of a video block. For example, a motion vector may indicate the displacement of a video block within a current video frame or picture relative to a prediction block within a reference frame associated with a current block being encoded within the current frame. The predetermined pattern may designate a video frame in a sequence as a P frame or a B frame. Intra BC unit 48 may determine a vector (e.g., a block vector) for intra BC coding in a manner similar to the motion vector determined by motion estimation unit 42 for inter prediction, or may utilize motion estimation unit 42 to determine a block vector.

[0048] Regardless of whether the prediction block is from the same frame according to intra-frame prediction or from a different frame according to inter-frame prediction, the video encoder 20 can form a residual video block by subtracting the pixel values ​​of the prediction block from the pixel values ​​of the current video block being encoded. The pixel difference values ​​forming the residual video block may include both luma component differences and chroma component differences.

[0049] Intra-prediction processing unit 46 may encode the current block using various intra-prediction modes, for example, during separate encoding passes, and intra-prediction processing unit 46 (or, in some examples, mode selection unit) may select an appropriate intra-prediction mode to use from the tested intra-prediction modes. Intra-prediction processing unit 46 may provide information indicating the intra-prediction mode selected for the block to entropy encoding unit 56. Entropy encoding unit 56 may encode the information indicating the selected intra-prediction mode into the bitstream.

[0050] After prediction processing unit 41 determines a prediction block for the current video block via inter-prediction or intra-prediction, adder 50 forms a residual video block by subtracting the prediction block from the current video block. The residual video data in the residual block may be included in one or more TUs and provided to transform processing unit 52. Transform processing unit 52 transforms the residual video data into residual transform coefficients using a transform (e.g., a discrete cosine transform (DCT) or a conceptually similar transform).

[0051] The transform processing unit 52 may send the resulting transform coefficients to a quantization unit 54. The quantization unit 54 quantizes the transform coefficients to further reduce the bit rate. The quantization process may also reduce the bit depth associated with some or all of the coefficients. The degree of quantization may be modified by adjusting a quantization parameter. In some examples, the quantization unit 54 may then perform a scan on the matrix including the quantized transform coefficients. Alternatively, the entropy coding unit 56 may perform the scan.

[0052] After quantization, entropy coding unit 56 entropy encodes the quantized transform coefficients into a video bitstream using, for example, context adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), syntax-based context adaptive binary arithmetic coding (SBAC), probability interval partitioning entropy (PIPE) coding, or another entropy coding method or technique. The encoded bitstream may then be sent to a video bitstream such as a Figure 1 The video decoder 30 shown, or archived as Figure 1 The video frame may be stored in storage device 32 as shown for later transmission to or retrieval by video decoder 30. Entropy encoding unit 56 may also entropy encode motion vectors and other syntax elements for the current video frame being encoded.

[0053] Inverse quantization unit 58 and inverse transform processing unit 60 apply inverse quantization and inverse transform, respectively, to reconstruct the residual video block in the pixel domain for use in generating reference blocks for predicting other video blocks. As noted above, motion compensation unit 44 may generate a motion compensated prediction block from one or more reference blocks of a frame stored in DPB 64. Motion compensation unit 44 may also apply one or more interpolation filters to the prediction block to calculate sub-integer pixel values ​​for use in motion estimation.

[0054] Adder 62 adds the reconstructed residual block to the motion compensated prediction block generated by motion compensation unit 44 to generate a reference block for storage in DPB 64. The reference block may then be used as a prediction block by intra BC unit 48, motion estimation unit 42, and motion compensation unit 44 to inter-predict another video block in a subsequent video frame.

[0055] Figure 3 1 is a block diagram showing an exemplary video decoder 30 according to some embodiments of the present application. The video decoder 30 includes a video data memory 79, an entropy decoding unit 80, a prediction processing unit 81, an inverse quantization unit 86, an inverse transform processing unit 88, an adder 90, and a DPB 92. The prediction processing unit 81 further includes a motion compensation unit 82, an intra-frame prediction unit 84, and an intra-frame BC unit 85. The video decoder 30 may perform the above-mentioned Figure 2 The encoding process is substantially the inverse of the decoding process described with respect to video encoder 20. For example, motion compensation unit 82 may generate prediction data based on motion vectors received from entropy decoding unit 80, and intra-prediction unit 84 may generate prediction data based on intra-prediction mode indicators received from entropy decoding unit 80.

[0056] In some examples, embodiments of the present disclosure may be dispersed in one or more of the units of the video decoder 30. For example, the intra BC unit 85 may perform embodiments of the present application alone or in combination with other units of the video decoder 30, such as the motion compensation unit 82, the intra prediction unit 84, and the entropy decoding unit 80. In some examples, the video decoder 30 may not include the intra BC unit 85, and the functions of the intra BC unit 85 may be performed by other components of the prediction processing unit 81, such as the motion compensation unit 82.

[0057] Video data memory 79 may store video data, such as an encoded video bitstream, to be decoded by other components of video decoder 30. Video data stored in video data memory 79 may be obtained, for example, from storage device 32, from a local video source (e.g., a camera), via wired or wireless network communication of video data, or by accessing a physical data storage medium (e.g., a flash drive or hard disk).

[0058] During the decoding process, the video decoder 30 receives an encoded video bitstream representing video blocks of an encoded video frame and associated syntax elements. The entropy decoding unit 80 of the video decoder 30 entropy decodes the bitstream to generate quantization coefficients, motion vectors or intra-frame prediction mode indicators, and other syntax elements. The entropy decoding unit 80 then forwards the motion vectors or intra-frame prediction mode indicators, and other syntax elements to the prediction processing unit 81.

[0059] When a video frame is encoded as an intra-prediction coded (I) frame or for intra-coded prediction blocks in other types of frames, the intra-prediction unit 84 of the prediction processing unit 81 can generate prediction data for a video block of the current video frame based on the intra-prediction mode transmitted by the signal and reference data from a previously decoded block of the current frame.

[0060] When the video frame is encoded as an inter-frame prediction coding (i.e., B or P) frame, the motion compensation unit 82 of the prediction processing unit 81 generates one or more prediction blocks for the video block of the current video frame based on the motion vector and other syntax elements received from the entropy decoding unit 80. Each of the prediction blocks can be generated from a reference frame in one of the reference frame lists. The video decoder 30 can construct the reference frame lists, i.e., List 0 and List 1, based on the reference frames stored in the DPB 92 using a default construction technique.

[0061] In some examples, when a video block is encoded according to the intra BC mode described herein, intra BC unit 85 of prediction processing unit 81 generates a prediction block for the current video block based on the block vector and other syntax elements received from entropy decoding unit 80. The prediction block may be within a reconstructed region of the same picture as the current video block as defined by video encoder 20.

[0062] Motion compensation unit 82 and / or intra BC unit 85 determine prediction information for a video block of the current video frame by parsing motion vectors and other syntax elements, and then use the prediction information to generate a prediction block for the current video block being decoded.

[0063] Motion compensation unit 82 may also perform interpolation using interpolation filters as used by video encoder 20 during encoding of the video blocks to calculate interpolated values ​​for sub-integer pixels of reference blocks. In this case, motion compensation unit 82 may determine the interpolation filters used by video encoder 20 based on the received syntax elements and use these interpolation filters to produce the prediction blocks.

[0064] Inverse quantization unit 86 inverse quantizes the quantized transform coefficients provided in the bitstream and entropy decoded by entropy decoding unit 80, using the same quantization parameters calculated by video encoder 20 for each video block in the video frame to determine the degree of quantization. Inverse transform processing unit 88 applies an inverse transform (e.g., an inverse DCT, an inverse integer transform, or a conceptually similar inverse transform process) to the transform coefficients to reconstruct the residual block in the pixel domain.

[0065] After the motion compensation unit 82 or the intra BC unit 85 generates a prediction block for the current video block based on the vector and other syntax elements, the adder 90 reconstructs the decoded video block for the current video block by adding the residual block from the inverse transform processing unit 88 to the corresponding prediction block generated by the motion compensation unit 82 and the intra BC unit 85. A loop filter 91 (e.g., a deblocking filter, an SAO filter, a CCSAO filter, and / or an ALF) may be located between the adder 90 and the DPB 92 to further process the decoded video block. In some examples, the loop filter 91 may be omitted, and the decoded video block may be provided directly to the DPB 92 by the adder 90. The decoded video blocks in a given frame are then stored in the DPB 92, which stores reference frames for subsequent motion compensation of the next video block. The DPB 92 or a memory device separate from the DPB 92 may also store the decoded video for later presentation on a display device (e.g., Figure 1 on a display device 34).

[0066] For ease of understanding, some terms involved in the exemplary embodiments of the present application are explained below.

[0067] The Motion Compensated Temporal Filter (MCTF) is an encoder-only video filtering technology that does not require any configuration changes to the decoder. It uses the temporal correlation of the video and the reference relationship between blocks to perform temporal filtering on the reference frame to reduce the temporal redundant information generated in the subsequent frame reference process. The core idea is to consider the subsequent temporal reference relationship, filter the reference frame, and encode the frame after MCTF filtering (i.e., MCTF frame) so that the decoded reconstructed frame is convenient for subsequent reference. That is, it replaces the encoded original frame with the filtered frame for all subsequent encoding processes.

[0068] Adaptive loop filtering (ALF) is a loop filtering tool in VVC, which is mainly used to reduce the mean square error between original pixels and reconstructed pixels. It is an adaptive filter based on Wiener filtering, that is, the encoder uses the reconstructed image encoded by the current frame and the target image (for example, the original image or MCTF image) to establish the Wiener-Hoff equation, and uses the least squares method to obtain the filter parameters, and then transmits the filter parameters to the decoder. The decoder uses the filter parameters to filter the reconstructed image to obtain the final reconstruction result, thereby reducing the decoding error. At the same time, due to the reference frame mechanism in video encoding, if the current frame is a reference frame, the reconstructed image after ALF filtering will also serve as a reference for subsequent frames, that is, the quality of the image after ALF filtering of the reference frame also affects the encoding efficiency of subsequent frames.

[0069] Sample Adaptive Offset (SAO), video coding standards (such as H.265 / HEVC, H.266 / VVC) use block-based transforms and quantize transform coefficients in the frequency domain. For strong edges in the image, due to the quantization distortion of high-frequency AC coefficients, ripples will appear around the edges after decoding. This distortion is called the ringing effect, which seriously affects the quality of the video. Sample adaptive compensation technology suppresses the ringing effect from the pixel domain: negative values ​​are added to compensate for the peak pixels that appear in the reconstructed curve, and positive values ​​are added to compensate for the trough pixels, so as to make the encoding as close to the original image as possible. The compensation value is calculated by the reconstructed image and the encoding target image (for example, the original image or MCTF image), and then transmitted to the decoding end. Similarly, due to the reference frame mechanism in video encoding, the quality of the image after SAO filtering the reference frame also affects the encoding efficiency of subsequent frames.

[0070] The present application takes into account: for reference frames, if loop filtering tools such as ALF and SAO use the original frame as the filtering target frame at the encoding end, that is, let the reconstructed frame be close to the original frame, the coding efficiency of the reference frame will be improved (because the reconstructed frame needs to calculate the distortion indicators such as PSNR and SSIM with the original frame), but the coding efficiency of subsequent frames will be reduced (because the MCTF filtering reference effect is not fully propagated to subsequent frames); if the loop filtering tool uses the MCTF frame as the filtering target frame at the encoding end, that is, let the reconstructed frame be close to the MCTF frame, the quality and coding efficiency of the reference frame will be reduced (because the reconstructed frame needs to calculate the distortion indicators such as PSNR and SSIM with the original frame), but the coding efficiency of subsequent frames will be improved. That is, whether the original frame or the MCTF frame is used as the loop filtering target frame, the highest joint coding efficiency of all frames (reference frames and subsequent frames) cannot be achieved. Therefore, the present application proposes a coding method for generating a loop filtering target frame by weighted summation of the original frame and the time domain filtering frame, which can comprehensively consider the coding efficiency of the reference frame and the subsequent frame and improve the overall coding performance. The following will be described in detail.

[0071] Figure 4 A flowchart of a video encoding method according to an exemplary embodiment of the present disclosure is shown.

[0072] Reference Figure 4 In step S401, the current frame is subjected to time domain filtering to obtain a time domain filtered frame.

[0073] As an exemplary embodiment, step S401 may include: performing MCTF on the original frame of the current frame to obtain an MCTF frame. It should be understood that the time domain filtering method may include but is not limited to MCTF.

[0074] In step S402, a weighted sum is performed on the original frame and the time-domain filtered frame of the current frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame.

[0075] As an exemplary embodiment, the loop filtering target frame may be generated by the following formula:

[0076] Target i =w1*Or i +w2*MCTFOr i ,

[0077] Among them, Target i Represents the brightness component or chrominance component of the i-th pixel in the loop filtering target frame, Or i Represents the brightness component or chrominance component of the i-th pixel in the original frame, MCTFOr i represents the brightness component or chrominance component of the i-th pixel in the time domain filtering frame, w1 represents the weight corresponding to the original frame, w2 represents the weight corresponding to the time domain filtering frame, and i is an integer greater than 0 and less than or equal to the total number of pixels.

[0078] As an example, 0≤w1≤1, w1+w2=1, when the weight w1=0, the loop filtering target frame degenerates into a time domain filtering frame, and when the weight w1=1, the loop filtering target frame degenerates into an original frame.

[0079] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame itself and the time-domain filtered frame itself to generate a loop filtering target frame.

[0080] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame after spatial filtering (i.e., the image frame obtained after spatial filtering of all or part of the original frame) and the time domain filtered frame after spatial filtering (i.e., the image frame obtained after spatial filtering of all or part of the time domain filtered frame) to generate a loop filtering target frame.

[0081] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame after spatial domain filtering and the temporal domain filtered frame itself to generate a loop filtering target frame.

[0082] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame itself and the time-domain filtered frame after spatial filtering to generate a loop filtering target frame.

[0083] As an example, the spatial domain filtering method may include, but is not limited to: Gaussian kernel filtering.

[0084] As an example, a 3x3 or 5x5 weighted window function may be used to perform spatial filtering on the original frame and / or the temporal filtered frame.

[0085] About the weighted weights used in weighted summation (i.e., the weights corresponding to the original frame and the weights corresponding to the time domain filtered frame)

[0086] As an exemplary embodiment, a preset weighted weight may be used. Specifically, the weight corresponding to the original frame may be a first preset value, and the weight corresponding to the time-domain filtered frame may be a second preset value.

[0087] As an example, the first preset value and the second preset value may be values ​​that are predetermined by experience, a large amount of data statistics, etc. to enable higher overall coding efficiency for all frames (reference frames and subsequent frames). For example, the first preset value and the second preset value may be 0.5.

[0088] As an exemplary embodiment, the weighted weights may be adaptively determined based on feature analysis. Specifically, the weights corresponding to the original frame and the weights corresponding to the time-domain filtered frame may be determined based on content features of the original frame.

[0089] As an example, the content characteristics may include, but are not limited to, at least one of the following items: noise characteristics, pixel mean, pixel variance, pixel gradient, mean of motion vector, variance of motion vector, quantization parameter QP in code rate allocation, and rate-distortion cost of transform coefficient TF after motion compensation MC.

[0090] As an example, the content features of the original frame can be input into the prediction model to obtain the weights corresponding to the original frame and / or the weights corresponding to the time-domain filtered frame output by the prediction model. For example, the prediction model can be determined by machine learning, and the machine learning samples may include: the content features of the video frame samples and the optimal weight labels, and the optimal weight labels can be determined based on the overall coding efficiency of all frames (reference frames and subsequent frames) corresponding to each weight.

[0091] The core principle of MCTF is to consider the temporal correlation between the reference frame and the subsequent frames, and perform temporal filtering (such as noise removal) on the reference frame to facilitate the reference of subsequent frames. However, due to the different characteristics of different video content, different weighting weights have different effects on loop filtering, so it is proposed to adaptively adjust the weighting weights according to the characteristics of the video content.

[0092] As an exemplary embodiment, weighted weights can be adaptively determined in combination with time domain characteristics. Specifically, the weight corresponding to the original frame and the weight corresponding to the time domain filtered frame can be determined based on the difference between the original frame and the time domain filtered frame, that is, based on the similarity between the original frame and the time domain filtered frame.

[0093] As an example, the weight corresponding to the original frame is positively correlated with the difference, and the weight corresponding to the time-domain filtered frame is negatively correlated with the difference. For example, the greater the pixel difference between the original frame and the time-domain filtered frame, the greater the weight corresponding to the original frame, and the smaller the weight corresponding to the time-domain filtered frame; the smaller the pixel difference between the original frame and the time-domain filtered frame, the smaller the weight corresponding to the original frame, and the greater the weight corresponding to the time-domain filtered frame.

[0094] As an exemplary embodiment, the weighted weights may be adaptively determined in combination with the spatiotemporal characteristics. Specifically, all or part of the original frame may be spatially filtered to obtain the original frame after spatial filtering, and all or part of the temporal filtered frame may be spatially filtered to obtain the temporal filtered frame after spatial filtering; then, the weighted weights are determined according to the pixel difference between the original frame after spatial filtering and the temporal filtered frame after spatial filtering. Accordingly, the weighted sum of the original frame after spatial filtering and the temporal filtered frame after spatial filtering is performed using the determined weighted weights to generate a loop filtering target frame.

[0095] According to the exemplary embodiments of the present application, the time domain and spatial domain characteristics are fully considered. For the spatial domain, the correlation between the pixels in the original frame and the surrounding pixels, and the correlation between the pixels in the time domain filtered frame and the surrounding pixels are considered; for the time domain, adaptive filtering methods such as bilateral filtering can be used to adaptively generate weighted weights based on the pixel differences between the original frame after spatial filtering and the time domain filtered frame after spatial filtering.

[0096] About loop filtering target frame

[0097] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame and the time-domain filtered frame to generate a target frame of the adaptive loop filtering tool applied to the current frame.

[0098] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame and the time-domain filtered frame to generate a target frame for the SAO tool applied to the current frame.

[0099] As an exemplary embodiment, step S402 may include: performing weighted summation on the original frame and the time domain filtered frame to generate a target frame of the adaptive loop filtering tool applied to the current frame and a target frame of the sample adaptive offset tool applied to the current frame, wherein the target frame of the adaptive loop filtering tool applied to the current frame and the target frame of the sample adaptive offset tool applied to the current frame are the same target frame.

[0100] As an exemplary embodiment, step S402 may include: performing a first weighted summation on the original frame and the time-domain filtered frame to generate a target frame of the adaptive loop filtering tool applied to the current frame; performing a second weighted summation on the original frame and the time-domain filtered frame to generate a target frame of the sample adaptive offset tool applied to the current frame; wherein the weighted weights used in the first weighted summation and the weighted weights used in the second weighted summation are determined respectively.

[0101] In step S403, based on the reconstructed frame and the loop filtering target frame of the current frame, filtering parameters of the loop filtering tool applied to the current frame are determined.

[0102] As an exemplary embodiment, the loop filtering tool may include but is not limited to at least one of the following items: an adaptive loop filtering tool, a sample adaptive offset tool.

[0103] As an exemplary embodiment, step S403 may include: determining filtering parameters of the adaptive loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and a target frame of the adaptive loop filtering tool applied to the current frame.

[0104] As an exemplary embodiment, step S403 may include: determining filtering parameters of the SAO tool applied to the current frame based on a reconstructed frame of the current frame and a target frame of the SAO tool applied to the current frame.

[0105] As an exemplary embodiment, step S403 may include: determining filtering parameters of the adaptive loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and a target frame of the adaptive loop filtering tool applied to the current frame; determining filtering parameters of the sample adaptive offset tool applied to the current frame based on the reconstructed frame of the current frame and a target frame of the sample adaptive offset tool applied to the current frame.

[0106] In step S404, the current frame is encoded based on the determined filtering parameters.

[0107] About weighted weight granularity

[0108] As an exemplary embodiment, the granularity of the weighted weights in the above-mentioned video encoding method may be sequence level, that is, the entire sequence shares the same weighted weights, and the weighted weights of different sequences may be different. For example, when the granularity of the weighted weights is sequence level, the weighted weights may be determined based on the content features of each original frame in the video frame sequence.

[0109] As an exemplary embodiment, the granularity of the weighting weights in the above-mentioned video encoding method may be frame level, that is, the entire frame shares the same weighting weight, and the weighting weights of different frames may be different.

[0110] As an exemplary embodiment, the granularity of the weighted weights in the above-mentioned video encoding method may be block-level, that is, the entire block shares the same weighted weight, and the weighted weights of different blocks may be different. For example, when the granularity of the weighted weights is block-level, the weighted weights may be determined based on the content features of the block.

[0111] As an exemplary embodiment, the granularity of the weighted weights in the above-mentioned video encoding method may be pixel-level, that is, the weighted weight corresponding to each pixel is determined, and the weighted weights of different pixels may be different. For example, when the granularity of the weighted weights is pixel-level, the weighted weights may be determined based on the content features of the pixel (for example, the difference between the pixel value of the pixel and the pixel mean).

[0112] In addition, the weighted weight granularity in the above video encoding method may also be other levels of granularity, for example, it may also be a band level.

[0113] About luminance and chrominance components

[0114] As an exemplary embodiment, the above video encoding method can be applied to both the luminance component and the chrominance component. As an example, the luminance component and the chrominance component can be weighted in the same or different manners, that is, the same or different weighting weights can be used.

[0115] As an exemplary embodiment, the above-described video encoding method may be applied to the luminance component alone.

[0116] As an exemplary embodiment, the above-described video encoding method may be applied to the chrominance component alone.

[0117] About the Loop Filter Tool

[0118] As an exemplary embodiment, the above video encoding method can be applied to all loop filtering tools. As an example, a unified target frame can be generated for all loop filtering tools, or a weighting method can be determined for each loop filtering tool and a required target frame can be generated accordingly.

[0119] As an exemplary embodiment, the above video encoding method may be applied to at least one loop filtering tool. As an example, the above video encoding method may be applied to an ALF loop filtering tool alone, or may be applied to an SAO loop filtering tool alone.

[0120] According to an exemplary embodiment of the present application, a method for generating a loop filtering target frame by weighted summing of an original frame and a time-domain filtered frame is proposed. When setting the loop filtering target frame of a reference frame (i.e., the current frame is the reference frame), the method jointly considers the coding efficiency of the reference frame and subsequent frames, thereby ensuring the coding efficiency of the reference frame while considering the coding efficiency of subsequent frames, achieving effective performance trade-offs, and ultimately improving the overall coding efficiency of the video.

[0121] Figure 5 A structural block diagram of a video encoding apparatus 500 according to an exemplary embodiment of the present disclosure is shown.

[0122] like Figure 5 As shown, the video encoding device 500 according to an exemplary embodiment of the present disclosure includes: a time domain filtering unit 501, a target frame generating unit 502, a parameter determining unit 503, and an encoding unit 504.

[0123] Specifically, the time domain filtering unit 501 is configured to perform time domain filtering on the current frame to obtain a time domain filtered frame.

[0124] The target frame generation unit 502 is configured to perform weighted summation on the original frame of the current frame and the time-domain filtered frame to generate a loop filtering target frame for a loop filtering tool applied to the current frame.

[0125] The parameter determination unit 503 is configured to determine the filtering parameters of the loop filtering tool applied to the current frame based on the reconstructed frame of the current frame and the loop filtering target frame.

[0126] The encoding unit 504 is configured to encode the current frame based on the determined filtering parameters.

[0127] As an exemplary embodiment, the weight corresponding to the original frame is a first preset value, and the weight corresponding to the time-domain filtered frame is a second preset value.

[0128] As an exemplary embodiment, the weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on content features of the original frame.

[0129] As an exemplary embodiment, the content feature includes at least one of the following items: noise characteristics, pixel mean, pixel variance, pixel gradient, motion vector mean, motion vector variance, quantization parameter in code rate allocation, and rate-distortion cost of transform coefficient after motion compensation.

[0130] As an exemplary embodiment, the weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on the difference between the original frame and the time-domain filtered frame.

[0131] As an exemplary embodiment, the weight corresponding to the original frame is positively correlated with the difference, and the weight corresponding to the time-domain filtered frame is negatively correlated with the difference.

[0132] As an exemplary embodiment, the target frame generation unit 502 may be configured to: perform weighted summation on the original frame itself and the time domain filtered frame itself to generate the loop filtering target frame; or, perform weighted summation on the original frame after spatial domain filtering and the time domain filtered frame after spatial domain filtering to generate the loop filtering target frame; or, perform weighted summation on the original frame after spatial domain filtering and the time domain filtered frame itself to generate the loop filtering target frame; or, perform weighted summation on the original frame itself and the time domain filtered frame after spatial domain filtering to generate the loop filtering target frame.

[0133] As an exemplary embodiment, the target frame generation unit 502 may be configured to perform weighted summation on the original frame and the time domain filtered frame to generate a target frame for the adaptive loop filtering tool applied to the current frame and / or a target frame for the sample adaptive offset tool applied to the current frame.

[0134] As an exemplary embodiment, the parameter determination unit 503 may be configured to: determine the filtering parameters of the adaptive loop filtering tool applied to the current frame based on the reconstructed frame of the current frame and the target frame of the adaptive loop filtering tool applied to the current frame; and / or determine the filtering parameters of the sample adaptive offset tool applied to the current frame based on the reconstructed frame of the current frame and the target frame of the sample adaptive offset tool applied to the current frame.

[0135] Regarding the video encoding device 500 in the above embodiment, the specific manner in which each unit performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0136] In addition, it should be understood that the various units in the video encoding device 500 according to the exemplary embodiment of the present disclosure may be implemented as hardware components and / or software components. Those skilled in the art may implement the various units, for example, using a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC), according to the processing performed by the defined various units.

[0137] Figure 6 FIG. 1 is a block diagram showing a structure of an electronic device according to an exemplary embodiment of the present disclosure. Figure 6The electronic device 600 includes: at least one memory 601 and at least one processor 602, wherein the at least one memory 601 stores a set of computer executable instructions, and when the computer executable instruction set is executed by the at least one processor 602, the video encoding method described in the above exemplary embodiment is executed.

[0138] As an example, the electronic device 600 may be a PC, a tablet device, a personal digital assistant, a smart phone, or other device capable of executing the above instruction set. Here, the electronic device 600 is not necessarily a single electronic device, but may also be any device or circuit capable of executing the above instruction (or instruction set) individually or in combination. The electronic device 600 may also be part of an integrated control system or system manager, or may be configured as a portable electronic device interconnected with a local or remote (e.g., via wireless transmission) interface.

[0139] In the electronic device 600, the processor 602 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller or a microprocessor. As an example and not limitation, the processor 602 may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0140] The processor 602 may execute instructions or codes stored in the memory 601, which may also store data. Instructions and data may also be sent and received over a network via a network interface device, which may employ any known transmission protocol.

[0141] The memory 601 may be integrated with the processor 602, for example, by placing RAM or flash memory within an integrated circuit microprocessor or the like. In addition, the memory 601 may include a separate device, such as an external disk drive, a storage array, or any other storage device that can be used by a database system. The memory 601 and the processor 602 may be operatively coupled, or may communicate with each other, such as through an I / O port, a network connection, etc., so that the processor 602 can read files stored in the memory.

[0142] In addition, the electronic device 600 may also include a multimedia resource display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.) All components of the electronic device 600 may be connected to each other via a bus and / or a network.

[0143] According to an exemplary embodiment of the present disclosure, a computer-readable storage medium storing instructions may also be provided, wherein when the instructions are executed by at least one processor, the at least one processor is prompted to perform the video encoding method as described in the above exemplary embodiment. Examples of computer-readable storage media here include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disk storage, hard disk drive (HDD), solid state drive (SSD), card storage (such as, multimedia card, secure digital (SD) card or extreme digital (XD) card), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk and any other device, any other device is configured to store computer programs and any associated data, data files and data structures in a non-transitory manner and provide the computer programs and any associated data, data files and data structures to a processor or computer so that the processor or computer can execute the computer program. The computer program in the above-mentioned computer-readable storage medium can be run in an environment deployed in a computer device such as a client, a host, an agent device, a server, etc. In addition, in one example, the computer program and any associated data, data files and data structures are distributed on a networked computer system, so that the computer program and any associated data, data files and data structures are stored, accessed and executed in a distributed manner by one or more processors or computers.

[0144] Figure 7 A computing environment 710 is shown coupled to a user interface 750. The computing environment 710 may be part of a data processing server. The computing environment 710 includes a processor 720, a memory 730, and an input / output (I / O) interface 740.

[0145] The processor 720 generally controls the overall operation of the computing environment 710, such as operations associated with display, data acquisition, data communication, and image processing. The processor 720 may include one or more processors for executing instructions to perform all or some steps in the above method. In addition, the processor 720 may include one or more modules that facilitate the interaction between the processor 720 and other components. The processor may be a central processing unit (CPU), a microprocessor, a single-chip microcomputer, a graphics processing unit (GPU), etc.

[0146] The memory 730 is configured to store various types of data to support the operation of the computing environment 710. The memory 730 may include predetermined software 732. Examples of such data include instructions for any application or method operating on the computing environment 710, video data sets, image data, etc. The memory 730 may be implemented by using any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0147] I / O interface 740 provides an interface between processor 720 and peripheral interface modules (e.g., keyboard, click wheel, buttons, etc.). Buttons may include, but are not limited to, a home button, a start scan button, and a stop scan button. I / O interface 740 may be coupled to an encoder and a decoder.

[0148] In an embodiment, a non-transitory computer-readable storage medium including, for example, a plurality of programs in a memory 730 and / or storing a bit stream generated by the above encoding method or a bit stream to be decoded by the above decoding method is also provided, wherein the plurality of programs can be executed by a processor 720 in a computing environment 710 to perform the above method. In one example, the plurality of programs can be executed by a processor 720 in a computing environment 710 to (for example, from Figure 2 The video encoder 20 in the computing environment 710 receives a bit stream or data stream including encoded video information (e.g., video blocks representing encoded video frames, and / or one or more associated syntax elements, etc.), and can also be executed by the processor 720 in the computing environment 710 to perform the above-mentioned decoding method according to the received bit stream or data stream. In another example, the multiple programs can be executed by the processor 720 in the computing environment 710 to perform the above-mentioned encoding method to encode the video information (e.g., video blocks representing video frames, and / or one or more associated syntax elements, etc.) into a bit stream or data stream, and can also be executed by the processor 720 in the computing environment 710 to (e.g., to Figure 3 Alternatively, a non-transitory computer-readable storage medium may store the bit stream or data stream generated by the encoder (e.g., Figure 2 The video encoder 20 in FIG. 1 generates a video signal for a decoder (eg, Figure 3A bitstream or data stream including encoded video information (e.g., video blocks representing encoded video frames, and / or associated one or more syntax elements, etc.) used by the video decoder 30 in the video decoder 30 when decoding video data. The non-transitory computer-readable storage medium can be, for example, a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0149] In an embodiment, a bit stream generated by the above encoding method or a bit stream to be decoded by the above decoding method is provided. In an embodiment, a bit stream including encoded video information generated by the above encoding method or encoded video information to be decoded by the above decoding method is provided.

[0150] In an embodiment, a computing device is also provided, which includes: one or more processors (e.g., processor 720); and a non-transitory computer-readable storage medium or memory 730 in which multiple programs that can be executed by the one or more processors are stored, wherein the one or more processors are configured to perform the above-mentioned method when executing the multiple programs.

[0151] In an embodiment, a computer program product having instructions for storing or transmitting a bitstream is also provided, wherein the bitstream includes coded video information generated by the above encoding method or coded video information to be decoded by the above decoding method. In an embodiment, a computer program product including, for example, a plurality of programs in a memory 730 is also provided, wherein the plurality of programs can be executed by a processor 720 in a computing environment 710 for performing the above method. For example, the computer program product may include a non-transitory computer-readable storage medium.

[0152] In an embodiment, the computing environment 710 may be implemented by one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs), FPGAs, GPUs, controllers, microcontrollers, microprocessors, or other electronic components for performing the above methods.

[0153] In an embodiment, a bit stream generation method is also provided, comprising: generating a bit stream according to the above-mentioned video encoding method.

[0154] In an embodiment, a computer program product is also provided, having instructions for storing a bit stream, wherein the bit stream includes: video data generated according to the above-mentioned video encoding method.

[0155] In an embodiment, a method for storing a bit stream is further provided, comprising: storing the bit stream on a digital storage medium, wherein the bit stream comprises encoded video information generated by the above-mentioned video encoding method.

[0156] In an embodiment, a method for transmitting a bit stream generated by the above video encoding method is also provided.

[0157] According to an exemplary embodiment of the present disclosure, a computer program product may also be provided. Instructions in the computer program product may be executed by at least one processor to implement the video encoding method as described in the above exemplary embodiment.

[0158] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0159] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A video encoding method, characterized in that: include: Perform time domain filtering on the current frame to obtain a time domain filtered frame; Performing weighted summation on the original frame of the current frame and the time-domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame; Determining filtering parameters of a loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and the loop filtering target frame; The current frame is encoded based on the determined filtering parameters.

2. The video encoding method according to claim 1, characterized in that The weight corresponding to the original frame is a first preset value, and the weight corresponding to the time-domain filtered frame is a second preset value.

3. The video encoding method according to claim 1, characterized in that: The weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on content features of the original frame.

4. The video encoding method according to claim 3, characterized in that: The content feature includes at least one of the following items: noise feature, pixel mean, pixel variance, pixel gradient, motion vector mean, motion vector variance, quantization parameter in rate allocation and rate distortion cost of transform coefficient after motion compensation.

5. The video encoding method according to claim 1, characterized in that: The weight corresponding to the original frame and the weight corresponding to the time-domain filtered frame are determined based on the difference between the original frame and the time-domain filtered frame.

6. The video encoding method according to claim 5, characterized in that: The weight corresponding to the original frame is positively correlated with the difference, and the weight corresponding to the time-domain filtered frame is negatively correlated with the difference.

7. The video encoding method according to claim 1, characterized in that: The step of performing weighted summation on the original frame of the current frame and the time-domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame comprises: Performing weighted summation on the original frame itself and the time-domain filtered frame itself to generate the loop filtering target frame; Alternatively, weighted summation is performed on the original frame after spatial domain filtering and the time domain filtered frame after spatial domain filtering to generate the loop filtering target frame; Alternatively, weighted summation is performed on the original frame after spatial domain filtering and the temporal domain filtering frame itself to generate the loop filtering target frame; Alternatively, a weighted sum is performed on the original frame itself and the time-domain filtered frame after spatial filtering to generate the loop filtering target frame.

8. The video encoding method according to claim 1, characterized in that: The step of performing weighted summation on the original frame of the current frame and the time-domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame comprises: Performing a weighted summation on the original frame and the time-domain filtered frame to generate a target frame of an adaptive loop filtering tool applied to the current frame and / or a target frame of a sample adaptive offset tool applied to the current frame; The step of determining the filtering parameters of the loop filtering tool applied to the current frame based on the reconstructed frame of the current frame and the loop filtering target frame comprises: Determining filtering parameters of the adaptive loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and a target frame of the adaptive loop filtering tool applied to the current frame; And / or, determining filtering parameters of the SAO tool applied to the current frame based on a reconstructed frame of the current frame and a target frame of the SAO tool applied to the current frame.

9. A video encoding device, characterized in that: include: A time domain filtering unit is configured to perform time domain filtering on the current frame to obtain a time domain filtered frame; a target frame generating unit configured to perform weighted summation on the original frame of the current frame and the time-domain filtered frame to generate a loop filtering target frame of a loop filtering tool applied to the current frame; a parameter determination unit configured to determine filtering parameters of a loop filtering tool applied to the current frame based on a reconstructed frame of the current frame and the loop filtering target frame; The encoding unit is configured to encode the current frame based on the determined filtering parameters.

10. An electronic device, characterized in that: include: at least one processor; at least one memory storing computer executable instructions, When the computer executable instructions are executed by the at least one processor, the at least one processor is prompted to execute the video encoding method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to perform the video encoding method according to any one of claims 1 to 8.

12. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by at least one processor, the video encoding method according to any one of claims 1 to 8 is implemented.

13. A method for generating a bit stream, characterized in that: include: A bit stream is generated according to the video encoding method according to any one of claims 1 to 8.

14. A computer program product having instructions for storing a bit stream, characterized in that The bitstream includes: Video data generated according to the video encoding method according to any one of claims 1 to 8.

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