18results about How to "Save transmission bandwidth" patented technology

A virtual pixel rendering method, a data transmission system, a control system and an electronic device relate to the field of display technology and solve the problem of display color cast. The method is implemented based on an RGB triangle arrangement structure, in which the sub-pixels in the same column are of the same primary color, and the sub-pixels in the same row are arranged in a circular pattern of three primary colors. Each sub-pixel forms a triangle structure with two adjacent pixels of different primary colors in the previous row, and forms a triangle structure with two adjacent pixels of different primary colors in the next row; each triangle structure is used as a display unit so that each sub-pixel is reused by six display units; the display data of each sub-pixel is the average of the original data of the corresponding pixel point of the sub-pixel in the image source and the corresponding pixel point in the image source in the left and right columns; or it is the weighted average of the original data of the corresponding pixel point of the sub-pixel in the image source and the corresponding pixel point in the image source in the left and right columns. The present invention can be applied to solve the color cast problem in a virtual display device.

The invention relates to a screen content image transmission method based on semantic communication, and belongs to the technical field of wireless communication and multimedia transmission. The method comprises the following steps: carrying out information source coding on an input text type screen content image through a coder; the method comprises the following steps of: carrying out weight distribution on code words after source coding through a weight distribution network, so that important semantic features are preferentially transmitted on a high-SNR (Signal to Noise Ratio) subcarrier; channel coding is carried out on the code words after weight distribution, and more transmission power is distributed for high SNR subcarriers in an OFDM (Orthogonal Frequency Division Multiplexing) transmitter; after the OFDM receiver receives the image, the text in the image is detected and recognized through the OCR and the scene text detection model, and the text level confidence coefficient is calculated; and designing a loss function based on the text level confidence, and protecting key text semantic features. According to the invention, the transmission quality of the image is improved, the transmission bandwidth is saved, and the problem that the traditional screen content image coding method is limited by the Shannon limit is solved.

The present invention relates to the field of image communication, and in particular to a video synchronization method based on image multi-dimensional feature value comparison. The method comprises the following steps: obtaining the original comparison video source, and performing discrete wavelet transform and image enhancement processing on it to generate enhanced video frames with higher quality; performing multi-dimensional feature encoding on the enhanced video frames to generate video feature vectors, and simulating protective transmission to obtain analog comparison videos at the receiving end; screening preliminary synchronization frame pairs by preset matching frame pair thresholds, and performing timestamp correction to generate accurate correction synchronization frame pairs. Based on the correction synchronization frame pairs, the enhanced video frames and the analog video at the receiving end are synchronized in the time domain and the feature coordinate space is compared. When the feature coordinates are consistent, a template error correction synchronization method is adopted; when they are inconsistent, a correction synchronization method is adopted; the present invention can achieve high-precision and high-stability video synchronization.

The method belongs to the technical field of panoramic monitoring of ultra-high voltage converter station, and aims to solve the problem that panoramic monitoring image data is directly uploaded to the cloud, occupying a large amount of cloud resources. By adopting multi-scale convolution blocks in the deep multi-scale residual network model to construct low-order and high-order features of images of various scales, the incomplete phenomenon of image detail extraction is avoided, and the residual learning mechanism is adopted to retain low-order rough features, thereby improving the reconstruction ability of the image. Topology optimization constructs the topology structure of the heterogeneous network, and the framework combining deep reinforcement learning and Monte Carlo tree search is used to construct the network according to the pre-defined topology rules. The search result of the Monte Carlo tree strengthens the learning of the deep convolutional neural network, so as to obtain more accurate prediction in the next iteration. After the data is processed in the edge side, it is transmitted to the cloud storage, saving the cloud storage space and transmission bandwidth.

This application relates to the field of network voice acquisition technology, and discloses a high-performance RTP voice acceleration acquisition method and system based on FPGA implementation. The method includes receiving raw IP packets and parsing them to obtain a set of key packet information containing five-tuple information, service type identifiers, and policy matching results; filtering out matching RTP voice packets and extracting the five-tuple information; and accessing the flow table in the first DDR4 memory through a multi-BANK interleaved parallel read / write engine to complete the query. When a flow table entry is empty, a table is created for the five-tuple flow, and a storage token corresponding to the second DDR4 storage address is requested. When a flow table entry matches, the timestamp is updated and the storage address is determined. Then, the RTP payload is extracted, written to the corresponding space, and counted. When the count reaches a threshold, an RTP voice compression frame is assembled and output. If the flow duration times out, the storage token is revoked; if the flow table entry times out, the flow table entry is revoked. This invention improves the rate of RTP voice acquisition and storage resource utilization, adapts to high-volume voice acquisition scenarios, and reduces server processing load.

Methods and systems for video processing are provided. In some embodiments, the method comprises: (i) receiving an input image; (ii) processing the input image by one or more convolutional layers; (iii) processing the input image by the plurality of residual blocks by using the division information of the input image as a reference to obtain a reference information feature; (iv) generating features of different scales based on the reference information features; (v) processing the features of different scales by a plurality of convolutional layer sets; (vi) processing the features of different scales by a reference spatial attention block (RSAB) to form a combined feature; and (vii) concatenating the combined feature with the reference information feature to form an output image.

The embodiment of the present application provides a kind of image format conversion method, device and video processing equipment.The method comprises the steps of: obtaining the image to be converted;Determine a plurality of pixel blocks and a plurality of encoding modes based on the image to be converted, wherein the plurality of encoding modes correspond to a plurality of mode index values;According to the luminance component deviation value of the pixel block under the plurality of encoding modes respectively, determine the target encoding mode of the pixel block, wherein the target encoding mode is one of the plurality of encoding modes;Based on the target encoding mode, a plurality of chrominance components of the pixel block are encoded to obtain a plurality of chrominance component output values of the pixel block;According to the target encoding mode, determine the target mode index value from the plurality of mode index values;Based on the target mode index value, a plurality of luminance components and the plurality of chrominance component output values, obtain target data and output.

The deep learning-based video multi-level adaptive compression cross-layer transmission optimization method and system of the application relates to the technical field of video transmission. By designing a compression level selection model based on deep learning, the optimal compression level is output based on the original video data and network environment parameters, and the corresponding compression strategy of the optimal compression level is obtained. A transmission strategy selection model is designed to generate a transmission strategy based on video quality parameters and network environment parameters. A global utility function is defined to calculate the global utility value when the compression strategy and the transmission strategy are assumed to be executed. An optimization objective function is designed, which inputs the compression strategy and the transmission strategy and outputs the optimized compression strategy and the transmission strategy. A condition judgment logic is set to select the final strategy based on the compression strategy and the transmission strategy before and after optimization, thereby achieving global optimization of video compression and transmission.

The invention provides a training method of a video enhancement model, a video enhancement method and related equipment, and relates to the technical field of video processing. The method comprises the following steps: acquiring a training video set; the training video set comprises a plurality of training videos, the training videos comprise a plurality of training video frame pairs, and each training video frame pair comprises a first training video frame and a second training video frame which are adjacent; performing enhancement processing on the first and second training video frames based on a video enhancement model to obtain first and second processed video frames; performing reconstruction processing on the first processed video frame and the second processed video frame based on a conductive encoder to obtain a reconstructed video frame and code rate information; determining loss information according to the reconstructed video frame and the second training video frame; and training a video enhancement model according to the loss information and the code rate information to obtain a trained video enhancement model. According to the method, a derivable encoder is introduced to train a video enhancement model, the video quality and the coded code rate are considered in the training process, and end-to-end optimization is achieved.

The present disclosure relates to a data transformation method, device, equipment and storage medium. The method includes obtaining at least two co-frequency signals; selecting a reference signal from the at least two co-frequency signals; determining the signal difference between the target signal and the reference signal; obtaining frequency domain data of the reference signal transformed from the time domain to the frequency domain, and using the frequency domain data and signal difference of the reference signal to obtain the frequency domain data of the target signal. Since the frequency domain data of the target signal can be obtained by referring to the frequency domain data of the reference signal, there is no need to perform a time domain to frequency domain transformation on the target signal other than the reference signal, and the frequency domain data of the target signal can be obtained, thereby greatly reducing the required computing resources and transmission bandwidth.

The present invention includes a cross-security zone data interaction method and system based on power system application grouping, which is used to realize cross-security zone data interaction of multiple business applications at the same time. The method includes: grouping server nodes of a production control zone and an information management zone by application according to the business; electing an application master node for data interaction according to a node application priority calculation formula within the application group; avoiding retransmission and missed transmission in abnormal circumstances of master-slave switching through a unified self-increment numbering synchronization mechanism; in the present invention, multiple business applications simultaneously perform cross-zone data interaction, which improves the efficiency of cross-zone interactive data, and the application master node within the application group interacts with data, which saves network transmission bandwidth and avoids the problem of multi-master mode's dependence on data sequence.

The invention discloses a wireless VR streaming super-division and frame prediction optimization method based on a visual model, and relates to the technical field of virtual reality and computer vision crossing. According to the method, a VR video viewport and a background area are split through VAE at a cloud end, a feature flow fusing a motion track is generated through a TNAM algorithm, a diffusion super-division model of causal sparse attention transformation is constructed, and a high-compression feature flow is output; end cloud collaboratively builds a dual-path frame prediction engine, and the cloud calculates time steps through RAFT optical flow, corrects artifacts in a large motion scene, and stabilizes subtitles in a static scene; the cloud feature flow is subjected to inverse VAE decoding at a terminal, and lightweight super-resolution is realized through three layers of U-Net and a CSTB module containing double cross-scale attention heads; and non-linear stretching is carried out on the edge pixel of the super-resolution rear view port based on the head posture, so that distortion correction is realized. According to the invention, through cloud high compression, terminal light super-resolution and collaborative dual-path optimization links, precise adaptation of bandwidth and image quality is realized, and the method has wide application value.

The present invention provides a light field image encoding and decoding method, system and device, which belongs to the field of image processing technology. It mainly collects key perspectives of each spatial position from the light field image, calculates the adjacency matrix reflecting the relationship between perspectives, encodes the key perspectives and the adjacency matrix to obtain a binary code stream. The present invention compresses some key perspectives, which can greatly improve the compression rate and reduce the size of the decoding cache. Through the correlation between different perspectives, graph learning can ensure the quality of the reconstructed light field image based on the adjacency matrix and improve the rate-distortion performance. Light field images are widely used in application fields such as environmental detection and medical imaging. Since the light field image data sampled in actual scenes can reach a large magnitude, it is urgent to design a compression algorithm to reduce the storage cost and reduce the transmission bandwidth. The module and algorithm proposed in the present invention have huge industrial potential.

This invention belongs to the field of data transmission and discloses a data transmission method, device, and storage medium. The method includes: extracting visual features of a target image and projecting the visual features into a latent low-dimensional space to obtain latent low-dimensional features; projecting the latent low-dimensional features into a semantic feature space based on a multi-level semantic encoder to obtain semantic features; performing category determination on the semantic features based on a first semantic knowledge base to obtain semantic errors; determining the target features of the target image based on the semantic errors; and sending the target features to a data receiving device. Because this invention extracts visual features of a target image, determines the target features of the target image based on the semantic errors corresponding to the visual features, and sends the target features to the data receiving device, compared to existing methods that directly send the target image to the data receiving device, the above method of this invention can reduce transmission latency and save transmission bandwidth.

The present invention relates to the technical field of data transmission, and provides a data transmission method for power distribution system equipment, including: obtaining power distribution data, the power distribution data including multi-dimensional power distribution data at several times in a day; analyzing the data fluctuations at each time according to the multi-dimensional power distribution data at several times in a day and dividing it into multiple time periods; obtaining the power load index of each time period based on the data fluctuations at all times in each time period; obtaining the compression priority of each time period according to the power load index of each time period; determining the data compression order of each time period within the day according to the compression priority of each time period, and compressing and transmitting according to the data compression order of each time period. This method can give priority to compressing data during peak power consumption periods, thereby reducing the required transmission bandwidth, improving data transmission speed and efficiency, and ensuring the timely transmission of key information.

The invention provides a vehicle remote monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: collecting multi-source vehicle data of a target vehicle at a vehicle end, selecting target vehicle state data according to the vehicle state data, superposing a camera video with the target vehicle state data for virtual screen rendering, and carrying out the virtual screen rendering. And generating a corresponding virtual screen video frame, unifying a timestamp for the virtual screen video frame, and in response to the detection that the driver and / or the target vehicle is in a predefined abnormal state, performing end-to-end encryption on the virtual screen video frame through a preset communication protocol and then transmitting the encrypted virtual screen video frame to the target terminal in real time.

An intraoral scanning system (102) includes a handheld intraoral scanning device (104). A handheld intraoral scanning device (104) captures intraoral scan data (110) associated with a user. The intraoral scan data includes texture data (110A) and three-dimensional (3D) data (110B) captured during an intraoral scan procedure of a user. The handheld intraoral scanning device (104) generates compressed texture data (112A) associated with the texture data (110A) based on applying the first compression operation (502) to the texture data (110A). The handheld intraoral scanning device (104) generates compressed 3D data (112B) associated with the 3D data (110B) based on applying the second compression operation (602) to the 3D data (110B). The handheld intraoral scanning device (104) transmits a combination of the compressed texture data (112A) and the compressed 3D data (112B) as compressed intraoral scanning data (112) to one or more client devices (106).

The invention discloses a data transmission method and device, equipment and a medium, relates to the technical field of energy storage, is applied to a battery cluster management unit, and comprises the following steps: responding to a data reading request sent by a battery array management unit, and determining a data transmission threshold value corresponding to the current charge state and the current current value of a battery cluster; judging whether the current battery data of each single battery in the battery cluster and the historical battery data transmitted to the battery array management unit last time meet a transmission condition set based on a data transmission threshold value or not; if yes, preprocessing the battery data between adjacent single batteries in an initial sequence formed based on the current battery data to obtain a processed sequence; and performing compression coding on the processed sequence by using a preset lossless compression algorithm to obtain compressed data, and transmitting the compressed data to a battery array management unit. The data transmission efficiency can be improved, transmission of invalid data is avoided, and unreliability caused by loss of historical data is avoided.