61results about How to "Achieve lossless compression" patented technology

The invention relates to a real time data compressing method, for compressing in-data packet data in a process control system, where the real time data comprises numerical values of analogue quantities and the method comprises: 1) initializing a dictionary, i.e. initializing characters that possibly occur during compressing into a dictionary; 2) reading in numerical valves; 3) making subtraction of adjacent data to obtain difference values and storing the first read-in numerical value in compressed files; 4) adopting LZW algorithm to compress the difference values. The invention realizes the lossless compression of real time data and the compressing course is safe and reliable. The invention has very good rapidness and can meet the requirements of real time databases and raises the history data inquiring efficiency.

The present invention discloses a compressing method of the data recorded by the electric power waveform. The compressing process includes the steps of: the collected data is performed by the integer small wave conversion based on the rising format and then all the data having been converted is coded in the Huffman method; the decompressing process includes the steps of: each pressing data that is read in bit is decoded in Huffman method, and then the data having been decoded is performed by the integer small wave contra-conversion. The present invention has the characteristics of a small amount of computing, a high compressing rate, a small distortion factor, a small occupied computer resources, etc. and the method can be realized in a flushbonding system. The compressibility and the distortion factor can be adjusted according to the demand and the flexibility of the using of the software is added. The present invention can also provide a threshold value to the detail information to realize the lossless compressing and the lossy compression. The electric power system waveform recording device in the present can realize a long-time and continuous recording waveform by combining the electric hardware technology under the situation of high sampling rate and big capability and the waveform can be transmitted far away through the communication interface reliably and quickly.

The invention provides an equivalent coordinative optimization method for a large-scale power grid dispatching plan. The optimization method comprises the steps as follows: (1) a large power grid is divided into a plurality of regional power grids, and the regional power grids are taken as equivalent nodes; (2) the regional power grids submit information of the equivalent nodes to the whole grid; (3) the whole grid determines a generation dispatching plan under the equivalent regional power grids, and issues a connecting line plan between the regions, planned total output of the regional power grids and a plan of a direct dispatching set; (4) the regional power grids calculate and determine output plans of regional sets according to the planned total output of the regional power grids, and calculate locational marginal cost; and (5) whether full-grid optimization is converged or not is judged through the marginal cost of two ends of a connection line, if so, calculation is ended, if not, the set which affects the grid security constraint corrects output bounds according to the optimization result and turns to the step (2). The iteration times can be controlled; the convergence is rapid; and rapid determination of the large power grid dispatching plan can be achieved.

The invention relates to a spatial-spectral associated prediction-based hyperspectral image lossless compression method, which comprises the following steps: conducting band combination to input hyperspectral images according to the magnitude of a spectrum correlation coefficient; selecting corresponding prediction algorithms according to different band combinations to eliminate correlation and to obtain a difference image; and conducting RICE entropy coding to the difference image to obtain a compressed code stream, storing or transmitting the compressed code stream and realizing reversible decoding locally or at other places. By adopting the method, the invention has the advantages that the spatial-spectral redundancy of the entire image can be effectively reduced, the calculated amountfor coding is reduced, no information is lost in the entire coding process, the lossless compression is realized, the lossless compression ratio of the hyperspectral image is improved, the storage resource required for image storage is reduced, the transmission bandwidth burden is reduced, the coding complexity is low, the hardware realization and the real-time transmission are facilitated and the error resilience is good.

The invention relates to an image lossless compression and decompression method based on lifting wavelet transform, belonging to the image compression field. The method comprises the following steps: the lifting scheme is utilized to obtain lifting wavelet, lifting wavelet transform is performed to an original natural image, the matrix transform of integer domain is completed to obtain restorable a wavelet coefficient which is an integer; and the wavelet coefficient is decomposed according to the characteristic of the wavelet coefficient to obtain low frequency coefficients and high frequency coefficients, and the obtained low frequency coefficients and high frequency coefficients are coded respectively so as to effectively increase the coding efficiency, wherein predictive coding is adopted for the low frequency coefficients and the SPIHT coding is adopted for the tree structure formed by the high frequency coefficients, thus the aim of lossless compression can be achieved and repeated comparisons in the SPIHT algorithm can be reduced. The method of the invention can increase the compression ratio and compression efficiency of the image as far as possible under the premise of ensuring that the image is undistorted.

A compressing encode method for a three-dimensional model texture based on Quardtree comprises the following steps: (1) dividing texture images according to Quardtree, resolving the texture images into a series of base textures with different resolutions, and coding the base textures; (2) arranging texture coordinates, and coding the texture coordinates successively. A decoding method corresponding to the coding method comprises the following steps: synchronously transferring texture data stream and geometric grid data, and decoding and recovering the texture data stream and the geometric grid data; and matching the texture data stream and the geometric grid data with geometrical model of the corresponding resolutions according to the textures with different resolutions. The compressing encode/decode method f of the invention has the advantages of high division efficiency, fast convergence rate as well as short client terminal responding and waiting time, and can control precision of model texture decode.

The invention belongs to the technical field of spectrum remote sensing, and provides a lossless spectrum image compression method based on support vector regression. The method comprises the following steps that firstly, an original image is guided in; secondly, a clustering algorithm is selected, classification preprocessing is carried out on the spectrum image, and a corresponding cluster index is acquired; thirdly, a prediction algorithm is selected, a prediction model is designed, and all pixels of the whole spectrum image are predicted according to the obtained cluster index and the prediction model so as to obtain a predicted image; fourthly, a differential method is adopted on the original image and the prediction image to obtain a residual image; fifthly, arithmetic coding is adopted on the residual image, the prediction coefficients obtained during prediction of the prediction model and the cluster index obtained through the clustering algorithm are coded to obtain a code stream file. According to the method, due to the fact that the read image is clustered, prediction models are established for all types, and the residual image and the side information are coded, the lossless spectrum compression based on support vector regression is achieved, a good lossless compression effect is achieved, the prediction accuracy is high, and the residual error is small.

The invention discloses a data encoding method and device and a storage medium. The data encoding method comprises the following steps: acquiring a to-be-encoded character string and a preset intervallength, wherein the to-be-coded character string comprises a plurality of first preset characters and a second preset character; determining a coefficient critical value according to a maximum numberof times of consecutive occurrences of the second preset character in the to-be-encoded character string; selecting an encoding coefficient less than the coefficient critical value from a preset coefficient list; determining a first encoding interval corresponding to the first preset characters and a second encoding interval corresponding to the second preset character according to the interval length and the encoding coefficient; encoding the to-be-encoded character string by using the interval length, the encoding coefficient, the first encoding interval and the second encoding interval toacquire an encoded value; and generating an encoded result according to the encoded value, and outputting the encoded result. Therefore, nondestructive compression of binary data can be well realized;and the data encoding method is high in compression capacity and good in compression effect.

The invention discloses a track compression method. The track compression method comprises the steps that S1, a track to be compressed is scanned, fixed points in the track to be compressed are obtained, the track is the path generated in the motion process of a moving object in space, and the fixed points are the starting point of the track or a road intersection or a terminal point; S2, a pre-configured frequent subsequent list is inquired, whether the subsequent fixed point of the fixed points in the track to be compressed is the most frequent subsequent fixed point of the fixed points or not is judged, the subsequent fixed point is the next fixed point adjacent to the fixed points, and if the subsequent fixed point of the fixed points in the track to be compressed is the most frequent subsequent fixed point of the fixed points, the step S3 is executed; S3, the most frequent subsequent fixed point is expressed with a negative number, and the set of the fixed points and negative numbers is obtained, and is adopted as the compressed track. Correspondingly, the invention provides a decompression method of the compressed track obtained through the track compression method. According to the track compression and decompression method, lossless compression of the high compression rate and high efficiency can be carried out on the track through track characteristics.

The invention discloses a data encoding/decoding method and device. The data encoding method comprises the following steps: acquiring a to-be-encoded character string, and adding a character 0 behindevery continuous N characters 1 in the to-be-encoded character string; performing division through a node between the adjacent characters 1 and 0, dividing the to-be-encoded character string into multiple sub-character strings; determining the corresponding encoding coefficient according to the occurrence amount of the continuous characters 1 of each to-be-encoded character string, and encoding each character in each character string according to the corresponding encoding coefficient, thereby obtaining an encoding interval lower limit value of the to-be-encoded character string. The encodingand decoding are performed through the multi-encoding coefficient, the nondestructive compression and reduction of the data are realized when the data compression efficiency is improved.

The embodiment of the invention discloses an image compression and decompression method and device, and the method comprises the steps of obtaining at least one image pair in a target image, wherein each image pair comprises any two adjacent frames of images in the target image; determining the pixel difference data between the two frames of images in the at least one image pair, sorting the pixeldifference data, and determining the sorted pixel difference data as the compressed data corresponding to a compressed frame image in the target image, wherein the compressed frame image is a frame image except a first frame image in the target image; and synthesizing the first frame of image in the multiple frames of images and the compressed data into a compressed image corresponding to the target image. The method also includes decompressing the generated compressed image by obtaining the pixel difference data. By adopting the image compression and decompression method and device, the display effect of the image can be ensured while the size of the image is reduced, the lossless compression of the image is effectively realized, and the network transmission consumption of the image in the application is reduced.

The invention provides an IntMDCT-based lossless audio encoding method and decoding method. The encoding method includes the following steps that: (1) audio time domain signals x (k) are framed, and a single frame of time domain signals x (k) can be obtained, wherein the k=0,..., N-1, wherein the N is frame length; (2) IntMDCT transformation is performed on the time domain signals, so that frequency domain signals X (m) can be obtained, wherein the m=0,..., N-1; and (3) Rice encoding is performed on the frequency domain signals, so that code streams can be obtained. The decoding method is an inverse process of the encoding method and includes the following steps that: firstly, Rice decoding is performed on an inputted code stream file, so that the frequency domain signals X (m) can be obtained, wherein the m=0,..., N-1; and secondly, IntMDCT inverse transformation is performed, so that the time domain signals x (k) can be restored, wherein the k=0,..., N-1. With the methods of the invention adopted, encoding parameters can be obtained adaptively, and the value of compression ratio is lower than that of block adaptive Rice, and the methods of the invention have a wider applicable range.

The invention discloses a data compression method and system for a wireless sensor network. Node data of the wireless sensor network is obtained; and conversion and drawing are carried out according to the node data, thereby obtaining an original signal. Mathematical morphological slicing is carried out on the original signal by employing a horizontal hierarchical slicing algorithm, thereby obtaining slicing data. Cluster analysis is carried out on the slicing data, thereby obtaining a slicing distribution curve of the original signal. According to the method and the system, the mathematical morphological processing is carried out on the waveform of the data collected by the wireless sensor network; the waveform of the original data is converted into the slicing distribution curve without changing the original data; the data scale is reduced; the lossless compression can be carried out on the large-scale data; and the application range is expanded.

The invention discloses a real-time centralized monitoring and management method for a distributed renewable energy power station, and belongs to the technical field of power systems and automation thereof. The method comprises the following steps: acquiring acquisition terminal data; data centralized parsing; data storing; data encryption; data uploading; and enabling data to enter a scheduling data network. The invention further discloses a real-time centralized monitoring and management system and equipment for the distributed renewable energy power station for implementing the method, anda readable storage medium storing the method. According to real-time centralized monitoring and management method for the distributed renewable energy power station provided by the invention, unifiedmonitoring, scheduling and management are carried out on the distributed renewable energy power station, the monitoring and management level of the renewable energy power generation station can be effectively improved, and the sustainable development of a country is facilitated.

The invention provides a compression method and device for skeletal animation data, and the method comprises the steps: obtaining the skeletal animation data of a virtual object, and obtaining the skeletal displacement data, skeletal rotation data and skeletal scaling data, corresponding to each key frame, of each skeletal node of the virtual object from the skeletal animation data; constructing afirst storage table corresponding to each key frame, and storing skeleton rotation data, corresponding to each key frame, of each skeleton node of the virtual object in the first storage table; constructing a second storage table corresponding to each key frame, and storing the skeleton identity identifier and the skeleton displacement data and/or the skeleton scaling data corresponding to at least one skeleton node subjected to displacement and/or scaling in the second storage table.

The embodiment of the invention discloses an image compression method and device, electronic equipment and a storage medium. The image compression method specifically comprises the steps of acquiring an image to be compressed; determining a target coding group of the to-be-compressed image, wherein the target coding group comprises a first coding method and a second coding method, and/or a third coding method and the second coding method; performing coding compression processing on the to-be-compressed image according to the first coding method and/or the third coding method in the target coding group to obtain a coding result parameters; and according to the second coding method in the target coding group, carrying out coding compression processing on the target coding result parameter in the coding result parameters again. According to the technical scheme provided by the embodiment of the invention, lossless compression of the image can be realized, the image compression rate and the image compression ratio are improved, and the image compression effect is further improved.

The invention discloses a time dimension compression method for a hyperspectral atmospheric infrared remote sensing image, and belongs to the technical field of remote sensing image compression. The hyperspectral atmospheric image compression method solves the problem that the existing hyperspectral atmospheric image compression method does not consider that the correlation rule between differenttime slices under large-range complex movement of the atmosphere is different from the correlation characteristic between high-frame-rate video frames, so that the image compression effect is poor. Based on the characteristic that hyperspectral infrared atmospheric image data detected by a detector in the same scene at different time have large correlation, a time dimension compression scheme of the hyperspectral infrared atmospheric image is designed based on an online learning prediction model. A prediction model from reference time slice images at different moments to a time slice image ata middle moment is established through a self-adaptive online updating prediction model, and prediction model parameters are updated in real time according to an online learning theory, so that multi-time slice image compression of hyperspectral data is realized, and the average compression ratio reaches 9.42. The inventioncan be applied to remote sensing image compression.

The invention discloses a lossless compression method for a large-format remote sensing image, and belongs to the field of image processing. The method comprises the following steps: dividing a large-format remote sensing image into independent coding regions which are not overlapped with each other; identifying the dynamic range of the pixel of each independent coding area, and determining the quantized bit number of the pixel; calculating a lossless compression parameter of each independent coding region according to the quantization bit number of each independent coding region; and according to the lossless compression parameter of each independent coding region, carrying out lossless compression on the independent coding region until lossless compression of the large-format remote sensing image is completed. According to the invention, a large-format remote sensing image is divided into a plurality of independent coding areas which are not overlapped with one another; the dynamic range of each independent coding area is identified as the local dynamic range of the large-format remote sensing image, the characteristic that the local dynamic range of the large-format remote sensing image is lower than the fixed dynamic range of the camera is effectively used, the overall lossless compression ratio is increased, compression parameters can be adjusted according to the local dynamic range, and lossless compression of the large-format remote sensing image is achieved.

The invention discloses a hyperspectral image distributed compression method and system based on compressed sensing. The hyperspectral image distributed compression method comprises the steps of conducting spectral compression sampling on an original hyperspectral image; carrying out distributed encoding processing on the sampled data; dividing each waveband into at least one coding block with thesame number, taking the first waveband as a starting waveband, carrying out linear prediction on the current coding block by utilizing the corresponding coding block in the adjacent previous wavebandfor any coding block in any of the rest wavebands, and determining the number r of LSBs needing to be transmitted by the current coding block according to the prediction residual error; and transmitting the data after spatial lossless compression of each coding block in the first waveband, the first r LSBs of each coding block in other wavebands and the prediction coefficient to a receiving end for compressed sensing reconstruction of the hyperspectral image. The compression method provided by the invention has relatively low complexity, good compression performance and error code resistance.With a coding block as a basic unit, an error code is controlled in the coding block and cannot be transmitted to other blocks.

The invention provides a binary coding method based on a standard Euclidean space and plane space projection mutual conversion characteristic. Based on basic characteristics of standard Euclidean space and two-dimensional plane space projection, two-dimensional plane space projection and I-Ching Sixty-four diagrams and I-Ching Sixty-four diagrams and binary data mapping, a binary data stream spatialization algorithm is adopted to generate ordered binary data streams based on I-Ching Sixty-four diagrams. High-speed and high-compression-ratio dimension-increasing encoding and lossless dimension-reducing decoding of any computer file are achieved, and the problems that in the technical field of electronic information at present, due to the existence of information exchange standard codes, a traditional compression algorithm based on the information theory is not high in file compression ratio due to limitation of information entropy, and the compression speed is low and the problems of lossless compression are solved.