47 results about "Run-length encoding" patented technology

The invention discloses a spatio-temporal data compression method and system based on lightweight processing, and relates to the technical field of image data processing, and the method comprises the steps: based on spatio-temporal data to be compressed, establishing standardized data entries, forming a window set through time axis segmentation, carrying out the periodic discrimination of windows according to the frequency domain energy distribution, and constructing spatio-temporal blocks, establishing an error control parameter table based on the global error budget; generating a time coding stream, performing integerization on the three-dimensional coordinates and the attribute values, generating a space coding stream through double difference and run length coding, performing edge folding lightweight and texture compression on the grid data, and generating a joint coding result; and based on a joint coding result, dividing the compressed data into a base layer and a plurality of enhancement layers, and establishing a relevance hierarchical storage structure and a block-level index table to generate the compressed data capable of being transmitted in a streaming manner. According to the method, collaborative compression can be carried out by utilizing spatial-temporal data internal relevance.

The invention relates to a pavement crack image skeleton extraction method based on an improved Zhang-Suen refinement algorithm. The method comprises the following steps: S1, carrying out binarization processing on a pavement crack image; s2, carrying out boundary expansion on the crack binary image; s3, carrying out run-length coding on the crack binary image in the horizontal direction, and carrying out compression storage on continuous non-zero pixel segments in each row; s4, using an improved Zhang-Suen refinement algorithm to process the crack binary image processed in the step S3; s5, removing boundary extension; s6, performing simplification processing on the preliminarily refined crack skeleton image by using four predefined 3 * 3 L-shaped structure templates; s7, removing burrs in the image; and S8, outputting a crack skeleton image. The technical problems that according to an existing skeleton extraction method, a topological structure is prone to being damaged, the calculation efficiency is low, the extraction result cannot be completely a skeleton with the single pixel width, and burrs exist in the skeleton extraction result are solved.

A point cloud encoding and decoding method and apparatus, and pertains to the field of point cloud processing technologies. The point cloud encoding method in embodiments of this application includes: An encoder determines, based on attribute information of target point cloud, a target attribute information distribution characteristic value corresponding to a target bit rate point, where the target bit rate point is a bit rate point corresponding to an attribute quantization step of the attribute information; the encoder determines a target run-length encoding manner based on the target attribute information distribution characteristic value; and the encoder performs encoding processing on the attribute information based on the target run-length encoding manner.

The invention provides a power plant high-frequency data transmission method based on a lossless compression algorithm. The power plant high-frequency data transmission method comprises the following steps of performing quality preprocessing on original high-frequency data; implementing hierarchical acquisition and periodic packaging according to data real-time requirements; performing differential coding for the data type: performing run-length coding on the switching value, and performing differential coding on the analog quantity; carrying out unified lossless compression on the coded data by using a Zstand-ard algorithm; the compressed data is encrypted and transmitted to an industrial internet platform, challenges confronted by a speed regulation system are handled through the steps, automatic optimization and dynamic adjustment of a data compression algorithm are achieved so as to adapt to the requirements of different application scenes, and the stability and efficiency of power production are improved.

The invention discloses a compression and decompression method for DNA sequencing data, and belongs to the technical field of biological information. The technical problems that in the prior art, when third-generation sequencing data are compressed, flexibility is poor, and the compression rate is low are solved. According to the compression method for the DNA sequencing data, global compression or block compression can be dynamically selected before compression, different compression methods are adopted for different types of data, and the flexibility of the compression method is improved; when the base sequence is compressed, the adopted self-indexing structure is a lossless compression method, the initial positions of all the sequences can be compressed and restored by using smaller data volume, and the compression rate is improved. Due to the fact that a special design is adopted in a run length coding structure, a character part is removed, an obtained run length segment is shorter, lossless compression of the position and the sequence is guaranteed, and meanwhile a better compression effect is provided. The method is mainly used for compression and decompression of DNA sequencing data.

This invention relates to a binary image compression and decoding method based on Base62 encoding. The method involves converting the original binary image to Base32 to generate a Base32 two-dimensional array; setting the number of compressed bytes; compressing the Base32 array in blocks according to the number of compressed bytes to create an index matrix; performing a first compression on the Base32 two-dimensional array based on the index matrix; and performing a second compression on consecutive empty data segments appearing in the first compression result, based on the characteristics of numerous white blocks and similar adjacent rows in printed labels, using run-length encoding and character substitution algorithms. The resulting binary image compression is lossless, achieving a high compression ratio. Furthermore, being based on Base62 encoding, it is suitable for network transmission. The Base62 encoding table is fixed, simplifying decoding and meeting the needs of narrowband transmission in the Internet of Things (IoT) and decompression requirements of low-performance terminals.

The invention discloses a WebGL-oriented hydrological grid data coding and rendering method and system, and relates to the technical field of water conservancy data visualization, and the method comprises the steps: carrying out the preprocessing of hydrological grid data, and carrying out the blocking according to a preset time length, and obtaining a plurality of time data blocks; performing joint coding of differential coding and run length coding on the water level data in each time data block, and performing polar coordinate quantization coding on the flow rate data in each time data block to obtain coded hydrological grid data; constructing a WebGL rendering pipeline based on pre-calculation and a double-buffering mechanism; and based on a WebGL rendering pipeline fragment shader, carrying out fusion rendering on the encoded hydrological grid data. The technical problems that the real-time interaction requirement cannot be met and the bandwidth is wasted in the prior art are solved.

The application provides a video image fast clipping and dimension reduction method and system based on a hierarchical bounding box, applied to the technical field of image processing, wherein the method collects multi-view dynamic scene point cloud data, and then divides the space by using a hierarchical bounding box to establish a bounding box structure with density characteristics; subsequently, optical diffraction array pre-filtering is used, and point clouds are separated based on wavelength selectivity and density distribution to generate a first subset and a background subset; then, adaptive pulse code modulation is used on nodes in the first subset to obtain high-precision data, and nodes in the second subset are compressed into low-code-rate data by using run-length encoding; subsequently, the two types of data are input into an improved k-d tree based on the spatial relationship of the bounding box to generate a two-dimensional point set representing key features, and a spatial index is constructed to realize real-time scene retrieval. The application can realize image dimension reduction while retaining key geometric features of the image, thereby improving efficient real-time spatial retrieval in a dynamic scene.

The invention discloses a generative image steganography method based on robust position mapping. According to the technical scheme, a steganography system composed of a run length coding module, an initial Gaussian noise generation module, a candidate pool processing module, a pseudorandom sequence generation module, an index sorting module, an information embedding module and a stable diffusion model SD is constructed. The run length coding module carries out run length coding on the secret information to obtain a two-tuple Y; an initial Gaussian noise generation module generates a Gaussian noise tensor zinit; the candidate pool processing module performs positive and negative value division on the zinit; the pseudo-random sequence module generates a random sequence P, and an index matrix S'is obtained through the index sorting module. The information embedding module embeds the secret sequence after run length coding in the Y into an empty tensor zemed to obtain a tensor zemed conforming to Gaussian distribution; and the SD carries out denoising on the zzzled and decodes the zzzled to generate a steganographic image. According to the method, the secret information extraction accuracy and steganography capacity can be effectively improved.

The invention relates to the technical field of industrial control system data storage, in particular to a self-adaptive block storage method based on data steady-state feature recognition, which comprises a block management module, a mode conversion module, an index module and a data IO (input / output) module. And performing data organization by adaptively using the time sequence main module A or the hybrid main module B based on the data steady-state characteristics. The time sequence main module A is suitable for a high-steady-state data sequence and compresses continuous steady-state data by adopting run length coding; the mixing main module B is suitable for a steady-state and discrete data mixing sequence, and the two types of data are distinguished and processed in a bitmap marking mode. Through the innovative architecture of the A / B main module, the discrete module, the high-speed index and the mode conversion, the technical problem that high compression ratio and high query performance in industrial time series data storage are difficult to consider at the same time is effectively solved, and the method is particularly suitable for efficient storage and retrieval of mass time series data in industrial 4.0 and edge computing scenes.

The application discloses a connected component marking method and device, electronic equipment and storage medium. The connected component marking method comprises the following steps: for the obtained image data, a corresponding row run index table and a run coding table are established; the run index table is scanned from top to bottom, and runs are processed row by row; the run coding table is traversed, and whether the current traversed run is adjacent to the first run of the last row is judged; if the run is adjacent to the first run of the last row, the connected component mark of the first run is assigned to the run, the equivalent relationship between the connected component mark of the current run and the connected component mark of other runs adjacent to the run after the first run in the last row is established, and the equivalence class table is updated; the run coding table is traversed again, if the connected component mark of the current traversed run is 0, a new connected component mark is established for the run, otherwise, the connected component mark of the run is updated by using the mark in the equivalence class table. According to the technical scheme provided by the application, the connected component marking method based on run coding is more efficient and occupies less resources.

A device and a method for buffering a graphical overlay to be applied to an image is disclosed. A graphical overlay description specifying content, size, and position in the image of a graphical element of the graphical overlay is obtained, and the graphical overlay is divided into a plurality of sequential line fragments. For each line fragment it is determined, using the graphical overlay description, whether the line fragment overlaps a part of the graphical element. On condition that the line fragment overlaps a part of the graphical element, information representing the part of the graphical element is buffered in a buffer memory for the line fragment. On condition that the line fragment does not overlap any part of the graphical element, a run-length coding representing identical pixels is buffered in the buffer memory for the line fragment.

This invention discloses a lossless data compression and encrypted transmission method based on federated middleware, belonging to the field of computer application technology. The method includes: performing run-length encoding on the data to be processed based on federated middleware to obtain first compressed data; processing the first compressed data using a compression algorithm based on a raw-middleware dual dictionary to obtain second compressed data. This compression algorithm uses both the raw dictionary and the middleware dual dictionary, adding only values ​​that appear at a set frequency to the dictionary; sequentially performing Huffman coding and DES processing on the second compressed data to obtain encrypted data and a key; performing RSA processing on the key to obtain an encrypted key; and transmitting the encrypted data and the encrypted key to the target end using an encrypted compression transmission plugin of an experiment-and-train-enabled architecture. This method achieves lossless data compression and encryption based on federated middleware, with fast algorithm speed and high security.

The invention discloses an image compression method and device, computer equipment and a computer readable storage medium, and the method comprises the steps: inputting a target image into a lossy image compressor for compression, and obtaining a lossy reconstructed image; calculating a residual image between the lossy reconstructed image and the target image; translating the residual image to a non-negative interval, and performing bit plane segmentation on the translated residual image to obtain a high-order part and a low-order part; according to a judgment result of whether the high-order part is all zero, performing run-length coding on the high-order part to obtain first compression information; estimating the probability distribution of the low-order part to obtain the probability distribution and a mask matrix corresponding to the probability distribution; and based on the state of an accumulation matrix, according to the to-be-coded pixel indicated by the mask matrix, compressing the low-order part to obtain second compression information. According to the embodiment of the invention, image lossless compression is realized.

The present invention proposes a data processing method, a data processing apparatus, an electronic device, and a computer-readable storage medium. The method includes: in response to a data processing instruction, segmenting an original data to obtain multiple data segments of the original data to enable parallel processing of the multiple data segments, wherein the multiple data segments includes a first data segment; determining whether the first data segment is suitable for using a preset run-length encoding; and when the first data segment is suitable for using the run-length encoding, using the run-length encoding to perform a run-length encoding processing on the first data segment. According to some embodiments, the original data is initially segmented into multiple data segments, and each data segment can be processed independently and concurrently, thereby enhancing the speed of data compression processing.

The invention provides a Blob image pixel boundary tracking method and device based on run length coding, and the method comprises the steps: determining a current run length corresponding to a current state of a target Blob image, and predicting a next run length corresponding to a next state according to a preset judgment condition, so as to achieve the state transition prediction; and extracting all position points included in the boundary from the current run to the next run to realize transfer operation. Therefore, according to the Blob pixel boundary tracking method based on run-length coding, the pixel boundary of the Blob image is calculated on the run-length coding, the calculation amount can be remarkably reduced, and the calculation efficiency of a traditional algorithm is improved.

The invention discloses a log data compression method and apparatus, an electronic device, a medium and a program product. The method comprises the steps of obtaining a log length of to-be-compressed log data; screening out a candidate log set with the same log length from a log length cache component; traversing the candidate log set according to a log queue reverse order mode, and dynamically selecting reference log data meeting a preset similarity threshold value from the candidate log set; performing XOR operation on the reference log data and the to-be-compressed log data to obtain intermediate log data; performing character reconstruction processing on the intermediate log data to generate character reconstruction log data; and performing run-length coding on the character reconstruction log data to obtain target compressed log data. Dynamic adaptation of the log structure can be achieved, efficient compression and rapid decompression of the log data are achieved, meanwhile, the burden of network transmission and early storage can be effectively reduced, and the method can be widely applied to the technical field of data processing.

The embodiment of the invention provides a data compression method and device based on a dynamic run mark, and the method comprises the steps: comparing an ith character in a to-be-compressed character sequence with an (i-1) th character, i being a positive integer greater than or equal to 1, and setting a 0th character in the to-be-compressed character sequence as an invalid value; if the ith character is the same as the (i-1) th character, 1 is set to be added to the counter, and the initial value of the counter is 0; if the ith character is different from the (i-1) th character, acquiring a value Q of a counter; under the condition that Q is larger than or equal to a threshold value, run-length coding is conducted on the (i-Q) th character to the (i-1) th character in the character sequence to be compressed, the highest bit of bytes representing the characters in the run-length coding is marked as 1, the number of bytes representing the number of times in the run-length coding is N, and the number of times is Q; and directly outputting the (i-Q)-th character to the (i-1)-th character in the to-be-compressed character sequence under the condition that Q is smaller than the threshold value.

The application discloses an image compression method and device, computer equipment and a computer readable storage medium. The method comprises the following steps: inputting a target image into a lossy image compressor to compress the target image and obtain a lossy reconstructed image; calculating a residual image between the lossy reconstructed image and the target image; shifting the residual image to a non-negative interval, and performing bit plane segmentation on the shifted residual image to obtain a high bit part and a low bit part; performing run-length encoding on the high bit part according to a judgment result of whether the high bit part is all zero to obtain first compression information; estimating a probability distribution of the low bit part to obtain the probability distribution and a corresponding mask matrix; and based on a state of a cumulative matrix, performing compression on the low bit part according to a pixel to be encoded indicated by the mask matrix to obtain second compression information. In the embodiment of the application, lossless compression of an image is realized.

There is provided a method of encoding a video signal, the method comprising: receiving an input frame; processing the input frame to generate at least one set of residual data, the residual data enabling a decoder to reconstruct the input frame from a reconstructed reference frame; and applying a run length encoding operation to the residual data set, where the run length encoding operation includes generating a run length encoded byte stream, the run length encoded byte stream including a set of symbols representing non-zero data values of the residual data set and counts of consecutive zero values of the residual data set. In some embodiments, the method includes applying a Huffman coding operation to the set of symbols. A decoding method and apparatus, and a computer readable medium are also provided.

The application discloses a compression method of marine grid data, and relates to the field of data processing.The method first performs mask calculation on target grid data, extracts a mask matrix and performs compression, so that position information of marine and land grids is separately stored, and the compression process of marine data is prevented from being disturbed by land data.Marine grid data is screened out according to the mask matrix, integer wavelet transformation is performed on the preprocessed data, and the wavelet transformation result is twice compressed by using run-length encoding and entropy encoding, so that the best compression ratio is achieved.Finally, the generated secondary compression file and the mask compression file are merged to form a final compression file.The application can achieve a higher compression ratio, meanwhile, ensures the quality and integrity of the data in the recovery process, and significantly improves the data storage and transmission efficiency.

The invention belongs to the technical field of artificial intelligence and data compression. In particular to a neural network parameter compression method based on bit-plane run-length coding, which aims at bit-level distribution characteristics of quantization parameters, and realizes efficient lossless compression through sign bit separation, negative non-sign bit flipping, high-bit-plane expansion and extended run-length coding. The method comprises the following steps: separating sign bits and flipping negative non-sign bits to optimize high-order sparsity; selecting the maximum m bit planes (m ranges from 2 to 5 and can be adaptively selected) from the next bit of the sign bit, and expanding the m bit planes into a one-dimensional bit stream according to columns; extended run length types of all zero segments, all one segment, a zero segment ending with a single 1 and a zero segment ending with two continuous 1 are adopted for coding, and the run length supports multi-gear self-adaptive bit width. A code stream formed by combining the low-order transparent transmission part, the sign bit and the run length code is output, and the efficiency can be further improved by combining numerical-level sparse coding. By optimizing bit plane distribution and a run-length mode, the compression rate is remarkably improved, hardware is easy and convenient to implement, and the method is suitable for storage and transmission of neural network weights and intermediate features and particularly suitable for end-side equipment with limited resources and efficient cloud storage scenes.

The invention discloses a point cloud coding method and device, a point cloud decoding method and device and communication equipment, and belongs to the technical field of point cloud processing, and the point cloud coding method comprises the steps that a coding end determines a target attribute information distribution characteristic value corresponding to a target code rate point according to the attribute information of a target point cloud, the target code rate point is a code rate point corresponding to the attribute quantization step size of the attribute information; the coding end determines a target run length coding mode according to the target attribute information distribution characteristic value; and the coding end carries out coding processing on the attribute information according to the target run length coding mode.

The application belongs to the technical field of image compression, and discloses a DCT coefficient processing circuit and method for image compression, which comprises an input module configured to receive DC coefficients and each AC coefficient of a pixel block; a coefficient code calculation module configured to calculate DC coefficient codes; a run statistics module comprising a reference pixel register and a run calculation unit; the run calculation unit is configured to: acquire reference AC coefficients and a reference run value in the reference pixel register; determine a target run value of a current pixel according to the reference AC coefficients and the reference run value; replace the reference AC coefficients with AC coefficients of the current pixel; replace the reference run value with the target run value of the current pixel; and a code length calculation module configured to calculate target binary codes and code lengths of the DC coefficients and each AC coefficient. When performing run encoding on the pixels, the application only needs to acquire AC coefficients and a run value of the previous pixel, thereby improving the efficiency of run encoding.

The embodiment of the invention provides an image compression method, a storage medium, an electronic device and a computer program product, and the method comprises the steps: converting a to-be-processed image into a plurality of first data trees, carrying out the minimization processing and difference processing of each node in the plurality of first data trees, and obtaining a plurality of second data trees, and performing bit plane coding and XOR processing on each node in the plurality of second data trees to obtain a binary coding matrix, and compressing the binary coding matrix based on run length coding to obtain a binary coding sequence. According to the embodiment of the invention, an image lossless compression scheme which is simple in computational logic and does not need additional storage space is designed, the complexity and resource cost of hardware implementation can be reduced, and the problems that in the related technology, a data lossless compression scheme is high in complexity and consumes a large amount of storage space and hardware resources are solved.

This application discloses a point cloud encoding and decoding method, apparatus, and communication device, belonging to the field of point cloud processing technology. The point cloud encoding method of this application includes: an encoding end determining a target attribute information distribution characteristic value corresponding to a target code rate point based on the attribute information of the target point cloud, wherein the target code rate point is a code rate point corresponding to the attribute quantization step size of the attribute information; the encoding end determining a target run-length encoding method based on the target attribute information distribution characteristic value; and the encoding end encoding the attribute information according to the target run-length encoding method.

The application discloses a kind of multi-mode adaptive block compression methods and systems for high-entropy satellite signal data, belong to data compression and satellite communication technical field.The application is firstly scanned to original satellite signal data globally linearly, identifies and extracts all run-length encoding sections satisfying minimum length threshold;Then carry out arithmetic progression detection and independent coding to the remaining gap;Then the data not captured are adaptively blocked, and the optimal difference mode is selected from subtraction difference and XOR difference based on the highest byte zero rate fast detection to preprocess;Finally, rANS byte plane coding and difference bit packing coding are synchronously executed to each data block, and compete with original straight-through mode, select optimal coding result output.The application realizes the consideration of high compression ratio and high throughput under the premise of guaranteeing lossless compression by two-stage decoupling RLE extraction and block-level multi-mode competition architecture, and has strict zero-inflation guarantee.

A compressor for compressing a control signal includes residual compression circuitry configured to sequentially receive a first control signal and a second control signal and perform compression based on a difference between the first control signal and the second control signal, coding mode determination circuitry configured to determine a coding mode based on a type of control signal, analog signal compression circuitry configured to perform compression based on indexing, and control signal compression circuitry configured to perform compression based on run-length encoding (RLE).

The application discloses a JPEG file secondary lossless coding method based on deep learning. First, the DCT quantization coefficient and related metadata are obtained by analyzing the JPEG file. Second, the DCT coefficient is grouped in the frequency domain and rearranged in the space to construct an autoregressive context. Then, the accurate probability distribution is generated through the deep learning network, and the mixed Gaussian and Laplace models are respectively used for different frequency bands. Then, the adaptive hybrid coding strategy is used to fuse the traditional run-length coding and the deep learning entropy coding. At the same time, the metadata such as the quantization table and the Huffman table are intelligently classified and efficiently compressed. Finally, the coding results are combined and packaged, and the decoding verification is realized to achieve the lossless reconstruction completely consistent with the original file. The method significantly improves the lossless compression rate of the JPEG file and has good adaptive ability.

The invention relates to the technical field of data transmission, in particular to an efficient data transmission method of a business hall computing power management device. The method comprises the steps of obtaining a target loss priority of a pixel point according to a difference value and an importance degree of the pixel point and a difference value of the pixel point on a row to which the pixel point belongs; according to the target loss priority, performing zero setting operation and run length coding on the difference value of the pixel points to obtain a comprehensive coding set corresponding to the image set; according to the occurrence frequency of each non-coding differential value in the comprehensive coding set, adjusting the non-coding differential values in the comprehensive coding set to obtain a target set of the image set; and performing Huffman coding on the target coding set of each image set corresponding to the business hall video to obtain compressed data, and transmitting the compressed data. And the transmission efficiency can be improved.