854 results about "Code rate" patented technology

The invention relates to the technical field of satellite communication signal processing, and discloses a broadband satellite signal blind demodulation reconstruction method and system based on sparse representation. The method comprises the following steps: carrying out frequency domain transformation on broadband satellite mixed signals to extract pilot frequency features to construct a beam state feature matrix, inputting the matrix into an adversarial network to generate a beam adaptive sparse dictionary, constructing a topological relation graph according to a Doppler frequency shift set, and carrying out collaborative sparse decomposition to obtain a sparse coefficient matrix; and extracting a code rate candidate set to execute parallel sparse reconstruction, determining an actual code rate through self-consistency verification to obtain a complete signal, analyzing a switching instruction, extracting time sequence statistical characteristics, predicting target domain characteristics, generating a switched sparse dictionary, and executing demodulation. The sparse decomposition precision, the code rate blind estimation accuracy, the cooperative processing efficiency and the switching continuity of the broadband satellite mixed signals are improved.

Methods, systems, and devices for wireless communications are described. A wireless device may perform a probabilistic shaping procedure using a shaping rate that is selected in accordance with a rule associated with a target spectral efficiency value, a modulation order, or both. Similarly, the wireless device may perform a channel coding procedure whose coding rate is selected in accordance with the rule. The rule may correspond to a relationship between the coding rate and the shaping rate. In some cases, the wireless device may select the shaping rate and the coding rate to be predefined values based on a target spectral efficiency value. In some examples, the wireless device may select the shaping rate and the coding rate based on a threshold coding rate, a quantity of punctured nodes used in the channel coding procedure, a quantity of layers corresponding to a multi-layer transmission, or any combination thereof.

The invention relates to the technical field of video coding and image processing, and discloses a code rate control method and system based on video image segmentation, and the method comprises the steps: carrying out the pixel-level semantic segmentation of a to-be-coded video frame sequence; extracting a foreground region of interest; calculating a corresponding segmentation uncertainty parameter; establishing semantic mutation parameters of the foreground region of interest; generating a semantic perception weight; executing region-level target code rate redistribution and quantization parameter mapping; and executing partition coding control. In the prior art, code rate control mainly depends on motion intensity or pixel complexity, and especially when a foreground target suddenly appears or disappears in a monitoring scene, a technical problem that a key target is blurred or a background code rate is wasted is easily caused. Due to the fact that the uncertainty modeling and semantic mutation sensing mechanism of the semantic segmentation result is introduced, priority coding of the foreground interest area is achieved under the frame-level code rate constraint condition, and the video coding quality and the code rate utilization efficiency are improved.

The invention discloses an intelligent household water processing terminal interaction control system based on 2.4 G hotspot networking, and particularly relates to the technical field of household water processing terminal interaction control. The overall system time sequence risk is accurately assessed by generating a time sequence consistency loss index, dynamic sampling adjustment, code rate optimization and control action rectification strategies are triggered based on the index, key data are uploaded preferentially, key control actions are executed preferentially, the problems of data transmission conflicts and time sequence lagging are effectively relieved, and meanwhile, the data transmission efficiency is improved. A node execution result and a control action receipt record are written into a state mirror image, the state mirror image and a time sequence consistency loss index are jointly evaluated to generate a safety degradation condition, and an executable safety strategy is synchronously issued, so that self-adaptive degradation and quick recovery of a system under abnormal conditions are realized, and continuity and stability of a water treatment process are ensured.

The invention discloses an extremely low bit rate image compression coding and decoding method of a stream matching diffusion model. The coding method comprises the following steps: acquiring an original image, and coding the original image into a compression latent variable and a hierarchical feature; based on the compression latent variable, generating an anchor point set and a mask parameter in a continuous domain; generating a visible index, a stream matching scheduling parameter and a confidence graph according to the compression latent variable, the hierarchical feature and the target bit rate; and combining the visible index, the anchor point set, the mask parameter, the stream matching scheduling parameter and the confidence map to form a code stream. According to the invention, through continuous domain mask and confidence gating reasoning of code rate perception, the method is suitable for image compression with an extremely low bit rate.

The invention relates to a target detection enhanced video code rate control method, and belongs to the technical field of video compression. The method comprises the following steps: preprocessing each frame of image of an input video, dividing a plurality of coding tree units in each frame of image, and calculating gradient features of the image and the coding tree units; the video is coded through different quantization parameters, and the code rate of the coded video and the distortion degree of the video are calculated; fitting a cubic logarithmic model to establish a relationship between the distortion degree and the code rate of the video by combining the gradient characteristics of each frame and the distortion degree and the code rate of the video; marking the ROI region of each image frame of the input video through a target detection network, and dividing the compensation level of the coding tree unit in combination with the ROI region and the gradient feature of the coding tree unit; and in combination with the compensation level of each coding tree unit, through a code rate allocation mechanism, allocating a coding code rate to each coding tree unit in each image frame of the input video. According to the invention, the video compression process can be optimized, and the overall performance of the compressed video is improved.

A zero-delay panoramic video bit rate control method that considers distortion temporal propagation aims to optimize target bit allocation and achieve global rate-distortion optimization in coding. It encompasses coding tree unit (CTU)-level bit rate control and temporal global rate-distortion optimization. CTU-level bit rate control involves optimizing target bit allocation and updating bit rate control parameters. Temporal global rate-distortion optimization utilizes the reconstruction error and motion compensation prediction error information of the previous coded frame to estimate the temporal dependence between CTUs in the current coding frame and those in the previous coded frame to adjust the coding parameters of the current CTU. The coding parameters are further fine-tuned according to the area stretching ratio encountered during the projection of the panoramic video from a 3D spherical surface to a 2D plane, taking into consideration the detrimental impact of interpolated redundant pixels on the coding process.

A system and method for enabling downlink signal transmission in a Multiple-Input Multiple-Output (MU-MIMO) system is provided. The method comprises of creating a scheduling information based on MU-MIMO Scheduling of a plurality of User equipments (UES), multiplexing the plurality of UES paired based on the scheduling decisions across time, frequency and code, inputting transport blocks of each UE pushed on to a Downlink shared channel (DLSCH), performing bit processing of each of the CRC encoded UEs, inputting Code-rate (MCS) for data modulation mapping on a post bit processed data, assigning DM-RS ports to the UE based on allocated MCS and number of antenna ports from a scheduling information structure, adding, a Partial Port Occupancy information (P-Poi) for each UE along with the scheduler information structure required for demodulation at UE and enabling optimal channel estimation at UE by adding new DM-RS port combinations using reserved fields in the DCI messaging.

The invention relates to the technical field of video compression, in particular to a narrow-bandwidth-based video monitoring data transmission and storage method, which comprises the following steps of: for an input video monitoring data frame, calculating a difference absolute value sum between a current frame and a reference frame; according to the method, the pixel difference of the current frame and the reference frame is calculated, and the average amplitude of the motion vector field is fused to form a comprehensive index of the dynamic degree of the quantized content, so that the image group structure is not fixed or periodic any more, and the dynamic degree of the quantized content can be calculated according to the score of scene activity and the change intensity. When a monitoring picture is static, a super-long image group is established to limit a compression code rate, when the picture is suddenly changed, the super-long image group is quickly switched to a short image group to ensure instant refreshing and definition of key information, meanwhile, non-uniform redistribution is performed on limited total code rate budget, bit resources can be intelligently inclined to frames with violent content change and large information amount, and the real-time refreshing and definition of the key information are ensured. Therefore, the subjective visual quality of the key dynamic moments is improved under the narrow bandwidth.

The invention provides a low-delay video stream code rate adaptation method and system based on off-line element reinforcement learning. The method comprises the following steps: constructing an off-line expert track data set; constructing a code rate adaptation strategy network, and outputting a downloading code rate selection result and a network throughput correction value by taking a video stream transmission state as input; and adopting a meta-implicit Q learning algorithm to perform double-layer alternate optimization of an inner layer and an outer layer on the policy network, the inner layer updating policy parameters of the policy network based on the offline expert trajectory data set, and the outer layer further adjusting the policy network parameters through meta reinforcement learning to improve the adaptability of the policy network to unseen tasks. According to the method, multiple expert algorithm experiences are integrated through offline reinforcement learning, high generalization and adaptive ability can be realized in multiple target time delays and complex network environments without online trial and error exploration, and finally, high-quality and smooth playing of video streams in a low-time-delay live broadcast scene is supported.

The invention relates to the technical field of video coding, and discloses a dynamic code rate control method based on deep learning and terminal equipment, and the method comprises the following steps: carrying out the feature extraction of a video frame through employing a convolutional neural network, recognizing a key region in a video, and distributing a coding weight for the key region according to semantic information, the convolutional neural network performs semantic segmentation on a video frame through a pre-trained semantic segmentation network, the video frame is divided into a plurality of semantic regions, different coding weights are allocated according to the importance of the semantic regions, a higher coding weight is allocated to a key region, and a lower coding weight is allocated to a non-key region. The long-short-term memory network is adopted to model and predict the network state indexes, so that the change trends of network states such as network bandwidth, packet loss rate and delay can be accurately predicted. And the code rate is adjusted in advance based on the prediction result, so that video coding can dynamically adapt to rapid change of a network environment.

The invention discloses a WebM protocol low-delay video and audio translation and subtitle optimization method and system, and belongs to the technical field of data processing, and the method comprises the steps: analyzing a WebM audio and video stream; establishing a video track-audio track association list and constructing a dynamic causal map; generating an initial translation text based on the audio frame sequence, the video frame sequence and the dynamic causal atlas, extracting lip movement and action semantic data of video frames through a reverse generation model to generate a completion translation text, and embedding SimpleBlock elements; defining a subtitle core gene, a non-core gene and a position gene according to the code rate data, the complete translation text and a user visual attention thermodynamic diagram, dynamically cutting the non-core gene based on code rate fluctuation, and adjusting the position gene in combination with the thermodynamic diagram to generate adaptive subtitle data; by synchronously playing and collecting feedback data, the edge weight and the subtitle position gene of the dynamic causal atlas are optimized. According to the invention, the robustness of audio and video translation and the self-adaptability of subtitle display are realized.

The invention discloses an AI-based motion subject tracking and streaming media optimization live broadcast system, and particularly relates to the technical field of motion subject tracking and streaming media optimization, AI-driven motion subject detection and tracking and streaming media coding adaptive control are closely fused, and code rate fluctuation of a coding end and bandwidth change of a network end are sensed in real time, so that the accuracy of the motion subject tracking and streaming media optimization live broadcast system is improved. A continuous and explainable live broadcast jitter risk analysis index is constructed, potential image quality jitter and delay risks are identified in advance through fusion of causal rule scoring and time sequence prediction, and the live broadcast jitter risk analysis index is directly mapped into an adaptive coding and transmission adjustment instruction. Priority guarantee, code rate distribution smoothing and delay control optimization of a key area are realized, the definition and playing smoothness of a live broadcast picture are remarkably improved, and sudden jitter and jamming phenomena are reduced.

The invention provides an on-site video return coding method and system, and the method comprises the steps: collecting a video stream of an on-site scene, judging whether a current video frame in the video stream responds to a scene switching video frame or not, and marking the current video frame as a key frame when the current video frame responds to the scene switching video frame; after the current video frame is identified as a key frame, visual saliency analysis is performed on the key frame, and an entropy weight matrix representing regional information importance distribution in the key frame is constructed according to a visual saliency analysis result and texture information entropies of different blocks in the key frame; adjusting code rate allocation weights of different blocks in the key frame according to the entropy weight matrix and a code rate regulation and control strategy of the key frame to obtain adaptive coding configuration adaptive to content characteristics of the key frame; and performing optimization coding on the key frame through adaptive coding configuration to obtain a target code stream in response to a field video return demand. By adopting the scheme of the invention, the dynamic differential coding of the key video frame in a complex scene can be realized.

The invention relates to the technical field of video monitoring, and provides an intelligent code rate control method for the field of indoor video monitoring, which comprises the following steps: S1, a camera continuously collects video streams of an indoor monitoring scene and pushes the video streams to a streaming media server; s2, decoding the received video stream data to obtain YUV format data, preprocessing the YUV format data, inputting the preprocessed YUV format data into a personnel dynamic detection model based on a deep learning algorithm, and identifying and outputting the motion state of indoor personnel; s3, a constant code rate factor CRF value of an encoder is adjusted in real time based on the personnel dynamic detection result, a low CRF value is adopted in a static scene to reduce the code rate, and the CRF value is adjusted in a graded mode according to the personnel number and the motion intense degree in a dynamic scene to improve the code rate; s4, writing the latest calculated constant code rate factor CRF value into an encoder, and performing intelligent decoding on the video stream data; and S5, carrying out storage or network transmission. And dynamically updating the constant code rate factor CRF value of the encoder according to the model detection result, thereby achieving the effect of balancing the code rate and the image quality.

The invention provides a physical frame structure design method suitable for satellite-ground high-order high-bit-rate wireless communication, which comprises the following steps of: slicing service data according to a preset length, and generating a baseband frame based on the obtained data slices; performing scrambling processing on the baseband frame to obtain a scrambled baseband frame; sequentially executing preset error correction coding processing on the scrambled baseband frames to obtain coded frames; performing internal interleaving processing on the coding frame to obtain internal interleaving data, and forming a first physical frame; performing external interleaving processing on the first physical frame to obtain external interleaving data; mapping the outer interleaved data into a symbol stream; performing physical frame framing based on the symbol stream to obtain a second physical frame; and performing scrambling processing on the to-be-scrambled symbols except the physical frame header in the second physical frame to obtain a scrambled physical frame, and performing modulation based on the scrambled physical frame to perform data transmission, thereby improving phase noise resistance and channel distortion resistance, enhancing Doppler frequency shift resistance, and optimizing transmission efficiency and reliability.

The invention relates to a dual-mode communication carrier signal modulation method and device based on an OFDM (Orthogonal Frequency Division Multiplexing) system, and the method comprises the steps: obtaining the signal-to-noise ratio of a plurality of subcarriers transmitted by a receiving end, and recognizing at least one target subcarrier of which the signal-to-noise ratio of the plurality of subcarriers is in a configured frequency band range, determining a target modulation mode according to the average value of the signal-to-noise ratio of the at least one target subcarrier; determining the bit mutual information of each target subcarrier according to the target modulation mode and the signal-to-noise ratio of the at least one target subcarrier, and correcting the bit mutual information of each target subcarrier based on the configured diversity times to obtain the corrected bit mutual information of each target subcarrier; calculating a bit mutual information average value according to the corrected bit mutual information of each target subcarrier, and determining a code rate of the to-be-modulated data based on the bit mutual information average value; and modulating the to-be-modulated data according to the code rate of the to-be-modulated data, the target modulation mode, the configured diversity times, the configured frequency band range and the target subcarrier.

The invention relates to the field of data transmission, and discloses a scheduling method for parallel transmission of multi-user video streams, which comprises the following steps of: decomposing each user video stream in a frame sequence layer, a code rate layer and a network buffer layer, and establishing a mapping unit for decomposed segments in a multi-dimensional state domain; based on the initial transmission situation map, asynchronous disturbance injection is carried out on the high-priority fragments; continuously monitoring the disturbance trajectory of the dynamic dependency scheduling layer in the flow, and identifying a delay abnormal region; mapping the generated semi-adaptive bandwidth allocation factor to a transmission node corresponding to each video stream in a network topology, and performing real-time regulation and control on a shunting proportion, a caching strategy and a priority weight of the transmission node through a nonlinear regulation function; in a dynamic scheduling topology convergence stage, joint integration is performed on a local bandwidth adjustment gradient and node topology weight attenuation. The method has the advantage of improving the continuity of multi-user video playing.

The invention discloses a video code rate dynamic allocation compression method based on content complexity prediction, which comprises the following steps of: S1, acquiring a video frame sequence, and preprocessing; s2, inputting the frame-level feature tensor into a gated residual convolutional network, and outputting a complexity prediction sequence; s3, constructing a frame priority queue, and calculating the complexity jump amplitude between adjacent frames; s4, a compression area is divided, and a corresponding code rate resource scale factor is allocated; s5, configuring a reference frame structure, a prediction interval and an initial quantization step size for each compression region, and calculating a region target bit number; s6, distributing regional bits to each frame in a compression coding process, and dynamically adjusting a frame-level quantization parameter and an entropy coding strategy; and S7, after compression is completed, reversely updating convolution prediction network parameters through bit distribution errors. According to the invention, fine code rate dynamic allocation and adaptive compression control based on content complexity are realized, and the video compression quality and bit utilization efficiency are effectively improved.

The invention relates to a self-adaptive information negotiation method applicable to a continuous variable quantum key distribution system, which comprises the following steps of: estimating an optimal code rate that an LDPC (Low Density Parity Check) code should reach under a current quantum channel, converting an initial code rate into the optimal code rate by a receiver, and obtaining a low-reliability bit number l which needs to be disclosed in conversion calculation, the method comprises the following steps of: decoding an LLR (Local Library Ratio) by using Bob, sending the LLR to Alice through a classic channel in combination with an encryption technology, sorting absolute values of the LLR by Alice in a decoding iteration process, selecting l bit positions with low reliability, sending the bit positions to Bob, determining a bit value by Bob according to the bit positions with low reliability sent by Alice, and feeding back and sending the bit value to Alice, and correcting the LLR value by Alice according to bit information sent by Bob. According to the method disclosed by the invention, the code rate of the LDPC code can be flexibly adjusted along with the change of the state of the time-varying channel, and the negotiation efficiency is improved, so that the key rate of the system is improved. The method is excellent in performance in a time-varying channel environment, negotiation efficiency under a low signal-to-noise ratio condition can be remarkably improved, and an efficient and reliable information negotiation scheme is provided for practical application of a quantum secret communication system.

The invention provides an ultra-low bit rate voice coding and decoding system based on text semantic information fidelity, and relates to the technical field of voice coding and decoding. The system comprises the following steps: performing voice feature extraction and text feature extraction on original voice through a multi-modal text-voice combined encoder to obtain voice features and text features, embedding the text features into the voice features to obtain text-voice features of the original voice, and performing voice feature extraction and text feature extraction on the original voice through a multi-modal text-voice combined encoder; sending the text-speech features of the original speech to a receiving end in a semantic communication system; and the receiving end inputs the received text-speech features into a text semantic fidelity decoder based on an attention mechanism to obtain reconstructed speech features and reconstructed text features, decodes the reconstructed speech features layer by layer, and performs attention calculation on the reconstructed speech features and the reconstructed text features to obtain decoded speech. By means of the voice coding and decoding technology, good voice perception quality can still be kept under the ultra-low code rate, and voice intelligibility is guaranteed.

The invention provides a video high-definition coding and low-delay transmission method for an IPTV (Internet Protocol Television) large-screen short play, which relates to the technical field of low-delay transmission, and comprises the following steps: defining an end-to-end measurement boundary and a time reference, configuring an acquisition mechanism of a network environment real-time state index, extracting high-definition coding metadata by adopting a coding end, and transmitting the extracted high-definition coding metadata to a transmission end; and timestamp information is marked and a unified structured operation state object is configured. A short window prediction path and a middle window prediction path are configured, confidence interval correction and lower limit fusion are combined to form a conservative available bandwidth estimation value, and when a network level label is judged to be a weak network level, a protection buffer mode and a low code rate pre-pulling strategy are triggered. The mechanism effectively solves the problems of frequent playing lagging and overhigh switching delay in a weak network environment in the prior art, so that a short play can still keep stable and continuous playing experience in a complex network environment.

The invention discloses a low-delay adaptive code rate control system for a meteorological monitoring video stream, and relates to the technical field of adaptive code rate control in video stream media transmission, and the system comprises a content importance analysis module which is used for carrying out the real-time analysis of a video block to be transmitted, generating a content importance score representing the meteorological information value; and the decision arbitration module is connected with the content importance analysis module and is used for receiving the content importance score, the network state information and the buffer area state information. According to the low-delay adaptive code rate control system for the meteorological monitoring video stream, bandwidth resources can be allocated according to the difference of meteorological information values of video contents, the quality of key monitoring pictures is guaranteed preferentially when network conditions fluctuate, unnecessary code rate switching is inhibited actively through internal look-ahead simulation and risk assessment, and the quality of the meteorological monitoring video stream is improved. Therefore, balance between continuous and clear transmission of high-value information and overall watching fluency is realized in a complex network environment.

A user equipment (UE) configured for operation in a fifth-generation new radio (5GNR) system may multiplex high-priority (HP) hybrid automatic repeat request acknowledge (HARQ-ACK) bits corresponding to a first HARQ-ACK code-book with low-priority (LP) HARQ-ACK bits corresponding to a second HARQ-ACK codebook onto a physical uplink control channel (PUCCH) transmission to a gNode B (gNB). The UE may be configured with the first HARQ-ACK codebook and the second HARQ-ACK codebook of different priorities. The HP HARQ-ACK bits may be encoded with a first maximum code rate (maxCodeRate) and the LP HARQ-ACK bits may be encoded with a second maximum code rate. The maximum code rates may be configured to the UE via RRC signalling per PUCCH format.

The invention discloses a VVC code rate control algorithm based on deep reinforcement learning, and the algorithm comprises the following steps: importing a video sequence into an encoder, and enabling the video sequence to enter initial frame coding; after the encoder completes the default encoding of the first two frames, the subsequent frame prediction firstly extracts the encoding state information of the previous prediction frame, and a greedy strategy is adopted to perform action selection; an overall reward value is obtained through CTU-level code rate control and an actual coding process in sequence; observing the next state and the last reward, performing TD iteration on the Q value, and adding the Q value into the Q value network after TD iteration; setting an experience playback pool; after the capacity of the experience playback pool reaches a threshold value, randomly sampling from the experience playback pool in batches; resetting the Q value network; and carrying out coding test based on the Q value network obtained by training. The VVC code rate control algorithm based on deep reinforcement learning has a good capability of guiding code rate control coding, and compared with standard code rate control in VTM13.0, the VVC code rate control algorithm based on deep reinforcement learning can bring high rate distortion performance and improve code control precision.

A communication method and device are disclosed. A terminal device receives first information, where the first information indicates N sets of first indexes, one of the N sets of first indexes includes M first indexes, the M first indexes include a first index, the first index corresponds to a first parameter, and the first parameter is for performing code rate compensation on uplink control information (UCI) carried in a subband full duplex (SBFD) time unit; and the first information further indicates P sets of second indexes, one of the P sets of second indexes includes Q second indexes, the Q second indexes include a second index, the second index corresponds to a second parameter, and the second parameter is for performing code rate compensation on UCI carried in an uplink time unit; and the terminal device sends UCI and uplink data based on the first parameter and / or the second parameter.

The invention discloses a congestion control method for dynamically adjusting a code rate growth factor based on reinforcement learning. The method comprises the following steps: step 1, collecting network feedback information in real time; 2, recording and feature extraction are carried out on the network state data of more than two continuous periods by adopting a sliding time window mechanism, and a multi-dimensional time sequence state vector capable of reflecting short-term dynamic change of the network is constructed; step 3, predicting an optimal code rate growth factor by the reinforcement learning model according to the current network condition; and step 4, respectively inputting the optimal code rate growth factor into a packet loss controller and a time delay controller, independently calculating a target code rate by the packet loss controller and the time delay controller according to respective judgment logics, and finally selecting a smaller value in outputs of the packet loss controller and the time delay controller as an actual sending code rate. According to the method, the problems of slow growth of the traditional GCC in a bandwidth recovery stage and overshoot instability of a learning algorithm can be effectively solved.

The invention discloses a high-definition video low-delay compression method based on self-adaptive adjustment, and aims to solve the problems of insufficient self-adaptive adjustment capability, too high encoding and decoding delay and low code rate and network bandwidth matching degree in the existing high-definition video compression technology. The method comprises the following steps: firstly, acquiring a high-definition video stream and a real-time network bandwidth parameter, extracting intra-frame texture complexity, inter-frame motion intensity and scene switching frequency characteristics, and constructing a two-dimensional adaptive compression strategy in combination with a real-time bandwidth; low-delay coding is executed by adopting parallel frame fragmentation and simplified adaptive arithmetic coding, adaptive code rate control is realized by combining code rate overflow early warning and intra-frame key region priority bit allocation, and finally, fast inverse transformation, quantization recovery and motion compensation optimization are completed at a decoding end based on strategy parameters synchronously transmitted at a coding end so as to reconstruct a high-definition video frame. According to the invention, the adaptive adjustment capability of video compression is improved, low time delay of coding and decoding is realized, and the method is suitable for real-time high-definition video transmission scenes such as remote monitoring and video conferences.

The invention discloses an intelligent super-division coding system for a low-bit-rate video, which comprises multiple stages of assembly lines and a merging module, each stage of the multiple stages of assembly lines is responsible for different GPUs / threads, and the multiple stages of assembly lines are integrated into a pipeline parallel task. The multi-stage assembly line comprises a video input and analysis module, a task segmentation and dynamic scheduling module, an AI super-division module, an HDR / SDR self-adaptive conversion module, a video coding module and a quality control and closed-loop optimization module which are sequentially processed. And time consistency and efficient utilization are ensured through dynamic scheduling, overlapping slicing and inter-frame constraint on multiple GPU hosts, so that the system can still improve subjective and objective image quality on the premise of remarkably reducing the code rate.

The invention relates to the technical field of general control or regulation systems, and discloses a multi-hardware collaborative ad hoc network video return control system, which comprises a PV pollution defense unit, a stability regulator, a control priority definition module and a code rate distribution unit, and is characterized in that the PV pollution defense unit removes local fault parameters before calculating a global instability index; controlling a priority definition module to monitor a user interface event to instantly update the priority; the stability regulator generates a single global regulation factor; according to the invention, open-loop competition is converted into closed-loop control, and the technical problems that the global control fails and the control instruction lags behind the command intention due to local faults are solved.