17results about How to "Improve encoding speed" patented technology

The invention relates to the technical field of video coding, in particular to a power system monitoring video rapid coding optimization method and system, and the method comprises the steps: extracting a plurality of maximum coding units of a power system monitoring video frame; a quantization parameter is introduced, and a deep learning-based adaptive multi-scale space prediction network is used to predict the maximum coding units to obtain an optimal sub-coding block division mode of each maximum coding unit; dividing the maximum coding unit according to the optimal sub-coding block division mode to obtain sub-coding blocks to be coded; performing mode prediction on the sub-coding block by using a texture sensing network to obtain an optimal intra-frame coding mode of the sub-coding block; and coding the sub-coding blocks of the monitoring video of the power system according to the optimal intra-frame coding mode to obtain coded video stream data. According to the method, the intra-frame prediction process is optimized by combining the adaptive multi-scale space prediction network and the texture sensing network, the coding complexity is reduced, and the video coding speed is remarkably improved while the image quality is ensured.

The invention provides a CU partition mode prediction method for a VVC coding unit and video coding equipment, and relates to the technical field of video coding. The prediction method comprises the steps that a CNN-RNN hybrid neural network model is constructed and trained, the CNN-RNN hybrid neural network model comprises a CNN module and an RNN module, the CNN module is used for extracting local texture features of a CU, and the RNN module is used for capturing a time sequence dependency relationship of the CU; inputting a to-be-coded CU into the CNN-RNN hybrid neural network model, and outputting a prediction result of a CU partition mode and a confidence score of the prediction result; based on the confidence score, the prediction result is selected as the final CU partition mode, or the RDO search is performed and the result of the RDO search is selected as the final CU partition mode. According to the method, the local texture features and the time sequence dependency relationship of the CU can be effectively extracted, and a final CU partition mode is selected according to the confidence score predicted by the model. On the premise of ensuring the coding efficiency, the calculation complexity is reduced, and the coding speed is improved.

The present invention proposes a fast memory encoding method based on a multi-synaptic plasticity pulse neural network, including: step one: converting external stimuli into an input pulse sequence based on a hierarchical encoding strategy; step two: after the pulse neural network receives the input pulse, the membrane potential of the output layer neurons is updated based on the improved SRM model; step three: using the supervised group Tempotron to update the synaptic weights between the input and the output layer, and activating the output layer neurons to memorize the input; step four: after the output layer neurons are activated, using unsupervised STDP to update the synaptic weights between the activated neurons in the layer to form an enhanced recurrent subnetwork to store memory; step five: while executing step four, using unsupervised inhibition of synaptic plasticity to update the synaptic weights between the inhibition layer and the output layer, and inhibiting feedback to ensure the separation of the firing time of neural groups with different inputs. The present invention also proposes a fast memory encoding device based on a multi-synaptic plasticity pulse neural network. The present invention effectively improves the encoding speed and stability of memory.

The invention discloses a VVC all-zero block skipping method based on a multi-level framework, which comprises the following steps of: reading a transformation coefficient from a transformation block TU, comparing the amplitude of the maximum transformation coefficient with a pre-calculated threshold value, if the amplitude is smaller than the threshold value, judging that a true all-zero block GAZB is generated, skipping a quantization and coding process, otherwise, judging that the GAZB is not generated; a non-GAZB skipping cost is calculated through a distortion optimization algorithm, whether a non-GAZB coding process is skipped or not is judged, if the normal coding cost is larger than the non-GAZB skipping cost, the block is judged to be a pseudo all-zero block PAZB for skipping, and otherwise, the block is judged to be a non-all-zero block NAZB; and in the calculation process of the dependent quantization DQ, all-zero detection is carried out by counting context features of the CG so as to skip the coding process in which the CG is detected to be all-zero. According to the method, a machine learning technology is not used, the calculation complexity is reduced under the condition that the coding quality is ensured, and the coding speed is increased.

The present application discloses a motion estimation method, device and electronic device, including: obtaining a target starting block corresponding to a prediction block to be predicted in a coding frame from a reference frame, wherein the target starting block is an image block in the reference frame used as a search starting position, and the matching cost between the target starting block and the prediction block reflects the motion intensity and texture complexity of the prediction block; obtaining a feature value of the prediction block, wherein the feature value reflects the texture complexity of the prediction block; determining a target integer pixel search algorithm based on the prediction block, the target starting block and the feature value; and searching for a target matching block from the reference frame based on the target integer pixel search algorithm with the target starting block as the search starting position. This method can effectively reduce the complexity of motion estimation under the premise of limited coding quality loss, so as to improve the overall coding speed of video coding processing.

The present disclosure relates to the field of computer technology, and in particular to a method and device for determining a coding mode of a coding unit CU, an electronic device, and a storage medium. The method is applied to high-efficiency video coding (HEVC), and the method includes: for a current CU to be coded in HEVC, determining a first rate-distortion cost of the current CU to be coded in a candidate advanced motion vector prediction (AMVP) mode; using an encoded CU with a coding dependency corresponding to the current CU to be coded, determining a second rate-distortion cost of the current CU to be coded in a candidate merge mode; based on the first rate-distortion cost and the second rate-distortion cost, determining a target coding mode corresponding to the current CU to be coded. The embodiments of the present disclosure can accelerate the rate-distortion cost optimization of the CU layer, and effectively improve the coding speed of the current CU to be coded.

The present disclosure provides an encoding method, an encoding apparatus, a decoding method, a decoding apparatus, a device and a readable storage medium, and it relates to the field of communication technology, so as to increase an encoding speed and a decoding speed. The encoding method includes: obtaining a feature image of a to-be-encoded image; obtaining a codebook range scaling factor in accordance with the feature image; obtaining a content-adaptive priori codebook range for each channel of the feature image in accordance with the codebook range scaling factor and a channel-adaptive priori codebook range for each channel; and performing entropy encoding on a target channel in accordance with an actual symbol range for the target channel of the feature image and a content-adaptive priori codebook range for the target channel, so as to form an encoded stream. The target channel is any channel of the feature image.

The embodiment of the invention provides a motion information determination method and device for inter-frame prediction, electronic equipment and a storage medium, and relates to the technical field of video coding. The method comprises the following steps: determining a plurality of reference blocks corresponding to a target coding block; in response to the reference block in an inter-frame prediction mode, acquiring corresponding first motion information as a motion information candidate; in response to the fact that the reference block is in the intra-frame prediction mode, acquiring second motion information selected during inter-frame prediction as a motion information candidate; generating a motion information candidate list of the target coding block; and performing distortion estimation on the motion information candidates in the motion information candidate list through distortion estimation search, and determining target motion information of the target coding block. According to the method, potential and valuable motion clues of motion information selected by an intra-frame prediction reference block during inter-frame prediction are mined. Therefore, the source of the candidate list is enriched, the quality of the motion estimation starting point can be effectively improved, and the compression efficiency and the coding speed are improved.

The invention provides an AIGC video coding method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a to-be-coded video based on the aliasing of a real foreground video and a pure background image, and adding noise matched with the real foreground video to a background region of the to-be-coded video; determining a current frame of the video to be coded; under the condition that the current frame belongs to the first image group, setting the pure background image as a first frame, encoding the pure background image to obtain encoding information, and under the condition that the current frame does not belong to the first image group, copying the encoding information of the first frame in a previous image group of the current frame as the encoding information of the first frame in the current image group; performing coding tree division on subsequent frames of the first frames of all the image groups of the to-be-coded video to obtain a coding tree; and determining the coding frame of the to-be-coded video based on the coding information of the first frame of each image group and the coding tree of each image group, thereby accelerating the video coding speed and reducing the coding complexity of video coding.

The embodiment of the invention provides a video coding method and device, electronic equipment, a storage medium and a computer program product, and relates to the technical field of image processing. The method comprises the following steps: acquiring a plurality of CTUs in a video frame to be coded; performing MCTF processing on the first CTU; in response to the completion of the MCTF processing by the first CTU, encoding the first CTU; and in response to completion of the MCTF processing by the first CTU, triggering at least one second CTU to perform the MCTF processing based on the reference association relationship corresponding to the first CTU. According to the method, MCTF processing is completed based on a CTU in a video frame to be coded, on one hand, a coding task corresponding to the CTU is triggered, and on the other hand, other CTUs are triggered based on a reference association relationship to carry out MCTF processing. The coding task and the MCTF task of each CTU are processed in parallel, so that the waiting time of the related coding task and the MCTF task is reduced, and the coding speed of the video frame is greatly improved.

The present invention discloses a parallel high-speed modulation and demodulation microwave transmission system based on LDPC coding, which relates to the field of communication technology, including a signal transmission platform, wherein the signal transmission platform is communicatively connected with a signal source module, an LDPC coding module, a parallel processing module, a diversity antenna module, a channel estimation and equalization module, a demodulation and decoding module, a signal processing module and a performance monitoring module, wherein the modules are connected with electrical signals; the signal source module is used to generate a high-speed data stream for transmission; the LDPC coding module is used to perform LDPC coding processing on the original data signal generated by the signal source module. The present invention improves the reliability of data transmission by introducing LDPC coding, so that a low bit error rate can be maintained under poor channel conditions or interference, and the application of parallel processing technology enables multiple sub-streams to be processed and transmitted independently, thereby reducing the impact of single path fading on the overall transmission quality.

The present disclosure provides a video encoding method and device, an electronic device and a computer-readable storage medium. The method includes: obtaining a current video to be encoded, the current video to be encoded includes a current image, the current image includes a current maximum coding unit, and the current maximum coding unit includes a current block; obtaining a hash value of the current block and an address of the current block in the current maximum coding unit; determining a target linked list whose hash index value matches the hash value of the current block from an intra-frame block copy hash table of the current maximum coding unit; excluding at least part of the invalid nodes in the target linked list according to the address of the current block in the current maximum coding unit, and obtaining the remaining nodes in the target linked list, wherein the invalid nodes correspond to candidate reference blocks in an uncoded area of ​​the current maximum coding unit; searching for a matching reference block of the current block from the remaining nodes to perform intra-frame block copy encoding on the current block.

The invention relates to a fractal image compression optimization method based on DCT (Discrete Cosine Transform) and compressed sensing, which comprises the following steps of: selecting an optimal matching block from image sub-blocks by combining a coding process of compressed sensing based on the low-frequency structure characteristic of an image; comprising the following steps: carrying out smoothness division on a D block according to low-frequency characteristics of image sub-blocks; according to the fractal coding method, measurement vector parameter calculation is carried out on different image sub-blocks to obtain horizontal / vertical measurement vectors, and then an optimal matching block is selected according to traversal matching of smooth sub-blocks by a method of combining correlation degree matching of the horizontal / vertical measurement vectors and traversal of smooth classes, so that the coding speed of fractal coding is greatly improved.

The present invention provides a Turbo encoding method and device, electronic device and storage medium, wherein the method comprises: encoding the serial output of the member encoder in the Turbo encoder in one dimension of the bit stream, extracting the time information, and based on the time information, converting the serial output of the member encoder into a two-dimensional generator matrix of the member encoder; based on the characteristics of the generator polynomial, converting the two-dimensional generator matrix into a plurality of partition matrices; based on each of the partition matrices and their corresponding preset lookup tables, parallel encoding the input information and then outputting it; the preset lookup table is a table listing all matching input vectors and output vectors corresponding to the partition matrices. The present invention obtains the encoding results of multiple consecutive input information at the same time through limited and few steps, greatly reducing power consumption, shortening encoding time, and using storage resources in exchange for increased encoding speed.

The invention discloses a high-definition video encoding acceleration algorithm based on an SVT-AV1 encoder, which comprises the following steps of: before an encoding frame enters a mode selection kernel ModeDecision Kernel, initializing a context model parameter into a default value in the mode selection configuration kernel ModeDecision Kernel; in a mode selection kernel ModeDecision Kernel, before a first super block (SB) of each row is coded, all reference frames in different reference lists are cyclically traversed, and the number numsbdelay of rows needing to lead coding of the reference frames is calculated according to the height of a motion search range area and the SB size SBSize; according to the calculated numsbdelay, judging whether the reference frame is coded with a sufficient number of SB or not; in the ModeDecision Kernel, after all the SBs of the first line are coded, the coded SB line of the current frame is set to be 0, and the current frame is sent to a reference frame queue, so that a subsequent coded frame referring to the frame enters a coding queue in advance; and in the ModeDecision Kernel, after the last SB of each row is coded, the identification bit (linear complex curPic) of the coded row, which corresponds to the frame, is updated, and after the last SB of each row is coded, the identification bit (linear complex curPic) of the coded row, which corresponds to the frame, is updated.

The present application provides a method, device, electronic device and computer-readable storage medium for determining a reference frame, including: determining the frame type of the image frame where the current block is located; obtaining the identifier of the reference frame of at least one adjacent block of the current block; using each single reference frame prediction mode to predict the current block respectively, and obtaining the rate-distortion cost corresponding to each single reference frame prediction mode; based on the frame type, the identifier of the reference frame of each adjacent block and the rate-distortion cost corresponding to each single reference frame prediction mode, obtaining the target reference frame template corresponding to each combined reference frame prediction mode; based on the target reference frame template corresponding to each combined reference frame prediction mode, determining the corresponding target combined reference frame when predicting the current block using each combined reference frame prediction mode. This scheme reduces the number of prediction combinations involved in the prediction in the process of selecting the optimal combined reference frame prediction combination, saves calculation time and improves the encoding speed.