Description: This file contains a new and improved version of the Huffman coder, (June 29. 2001). The name is Huff06.m. There are also some additional files which are helpful when using Matlab for data compression: quantizer, different variants of run-length-encoding and end-of-block coding in Mat2Vec, and a program which do JPEG-like entropy coding. A complete compression example is shown in TestMat2Vec.m. This file is all you need for Huffman coding in MatLab.-This file contains a new and improved version of on of the Huffman coder, (June 29. 2001). The name is Huff06.m. There are also some additional files which are helpful wh en using Matlab for data compression : quantizer. different variants of run-length-encoding an d end-of-block coding in Mat2Vec. and a program which do JPEG-like entropy coding . A complete compression example is shown in Tes tMat2Vec.m. This file is all you need for Huffma n coding in MatLab. Platform: |
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Author:金金 |
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Description: This file contains a new and improved version of the Huffman coder, (June 29. 2001). The name is Huff06.m. There are also some additional files which are helpful when using Matlab for data compression: quantizer, different variants of run-length-encoding and end-of-block coding in Mat2Vec, and a program which do JPEG-like entropy coding. A complete compression example is shown in TestMat2Vec.m. This file is all you need for Huffman coding in MatLab.-This file contains a new and improved version of on of the Huffman coder, (June 29. 2001). The name is Huff06.m. There are also some additional files which are helpful wh en using Matlab for data compression : quantizer. different variants of run-length-encoding an d end-of-block coding in Mat2Vec. and a program which do JPEG-like entropy coding . A complete compression example is shown in Tes tMat2Vec.m. This file is all you need for Huffma n coding in MatLab. Platform: |
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Author:金金 |
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Description: 通过测量小波变换产生图像的熵、方差、最大值、最小值、平均值及各子图像内小波变换系数间的相关性来确定各子图像应采取的编码策略-Wavelet transform generated by measuring the image entropy, variance, maximum, minimum, average and sub-image with the wavelet transform coefficients of correlation between each sub-image to determine the encoding strategy should be taken Platform: |
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Author:gyq |
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Description: 熵编码源程序，集常见的熵编码方式于一起，很实用。-Entropy coding source, commonly seen in with entropy encoding, it is practical. Platform: |
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Author:terry |
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Description: 运动估计是视频编码的关键技术，其最基本的原理是利用相邻帧间的时间
相关性，通过预测来减少时间冗余度。在实际编码中，为了节省码率，并不传
输每一帧的全部数据，而是利用运动估计求出每一帧与其预测参考帧之间的差
值。运动估计越准确，差值的分布越趋近与零，差值块的能量越小，经过变换、
量化和熵编码后所产生的码流的比特位率也越少。因此，运动估计搜索的准确
程度直接影响到了编码的压缩性能。
-Motion estimation is the key to video encoding technology, its basic principle is the use of the adjacent time frame relevant, through the forecast period to reduce redundancy. In the actual code, in order to save bit rate and does not transfer all the data of each frame, but the use of motion estimation for each frame obtained with the prediction of the difference between the reference frame. Motion estimation more accurate, more closer to the margin and the distribution of zero, the smaller the energy difference between blocks, after transform, quantization and entropy coding of the code produced by the bit stream bit rate is less. Therefore, the motion estimation search accuracy of the direct impact on the performance of the compression coding. Platform: |
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Author:罗鹏 |
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Description: In computer science and information theory, Huffman coding is an entropy encoding algorithm used for lossless data compression Platform: |
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Author:hazhiriq200 |
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Description: 视频信号熵编码源程序
熵编码法是一种进行无损数据压缩的技术，在这个技术中一段文字中的每个字母被一段不同长度的比特(Bit)所代替。与此相对的是LZ77或者LZ78等数据压缩方法，在这些方法中原文的一段字母列被其它字母取代。
每个字母按照其出现的可能性所获得的最佳比特数取决于熵。
本程序不仅提供源程序，还提供相应的实例。-Entropy coding the video signal source for entropy coding method is a lossless data compression technology in the technology section of the text in each letter is a bit different lengths (Bit) replaced. In contrast the LZ77 or LZ78 data compression method, etc., in these methods section of the original letters column is replaced by other letters. Each letter appears in accordance with its possibilities to obtain the optimal number of bits depends on the entropy. This procedure provides not only source, but also provide examples. Platform: |
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Author:安慰安防 |
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Description: Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol. It was developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". Platform: |
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Author:Abirami |
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Description: In computer science and information theory, Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol. It was developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". Platform: |
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Author:vishnu |
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Description: MTF变换，一种字节数据流编码方式，用来改善加密压缩性能-The move-to-front transform (or MTF) is an encoding of data (typically a stream of bytes) designed to improve the performance of entropy encoding techniques of compression. When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithms. Platform: |
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Author:sununjoy |
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Description: Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol. It was developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes Platform: |
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Author:yashika |
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Description: 本程序主要是实现图像的游程编码。游程编码是JPEG等图形图像标准中常用的熵编码方案-This program is run-length coding of the image. RLE is used in JPEG and other graphic images standard entropy encoding scheme Platform: |
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Author:吴广哲 |
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Description: 熵编码(entropy encoding)是一类利用数据的统计信息进行压缩的无语义数据流之无损编码。本章先介绍熵的基本概念，然后介绍香农-范诺(Shannon-Fano)编码、哈夫曼(Huffman)编码、算术编码(arithmetic coding)、行程编码(RLE)和LZW编码等常用的熵编码方法。 哈夫曼编码建议了一种将位元进位成整数的算法，但这个算法在特定情况下无法达到最佳结果。为此有人加以改进，提供最佳整数位元数。这个算法使用二叉树来设立一个编码。这个二叉树的终端节点代表被编码的字母，根节点代表使用的位元。除这个对每个要编码的数据产生一个特别的表格的方法外还有使用固定的编码表的方法。比如加入要编码的数据中符号出现的机率符合一定的规则的话就可以使用特别的变长编码表。这样的编码表具有一定的系数来使得它适应实际的字母出现机率。-Entropy coding (entropy encoding) is a kind of use data of statistical information compression without semantic data flow of nondestructive coding. This chapter first introduces the basic concept of entropy, and then introduce Shannon- occupies (Shannon- Fano) coding, Huffman (Huffman) coding, arithmetic coding (arithmetic coding), stroke encoding (RLE) and LZW encoding used entropy coding method. Huffman encoding suggest a bit carry into integer algorithm, but this algorithm in specific cases not to achieve the best results. Therefore some improved, providing the best integer bit number. This algorithm using binary tree to set up a code. The binary tree terminal node representing the code letters, on behalf of the root node used bits. In addition to this for each to coded data to create a special form of the method and use fixed code table method. Such as join to coding data symbols appear probability accord with certain rules words can use special variable ChangBian chart. This code Platform: |
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Author:杨飞帆 |
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Description: Arithmetic coding is a form of entropy encoding used in lossless data compression. Normally, a string of characters such as the words "hello there" is represented using a fixed number of bits per character, as in the ASCII code. When a string is converted to arithmetic encoding, frequently used characters will be stored with fewer bits and not-so-frequently occurring characters will be stored with more bits, resulting in fewer bits used in total. Arithmetic coding differs from other forms of entropy encoding such as Huffman coding in that rather than separating the input into component symbols and replacing each with a code, arithmetic coding encodes the entire message into a single number, a fraction n where (0.0 ≤ n < 1.0). Platform: |
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Author:bhushan |
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Description: Huffman coding and Compression algorithm c++ code
In computer science and information theory, a Huffman code is an optimal prefix code found using the algorithm developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper A Method for the Construction of Minimum-Redundancy Codes .[1] The process of finding and/or using such a code is called Huffman coding and is a common technique in entropy encoding, including in lossless data compression. The algorithm s output can be viewed as a variable-length code table for encoding a source symbol (such as a character in a file). Huffman s algorithm derives this table based on the estimated probability or frequency of occurrence (weight) for each possible value of the source symbol. -Huffman coding and Compression algorithm c++ code
In computer science and information theory, a Huffman code is an optimal prefix code found using the algorithm developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper A Method for the Construction of Minimum-Redundancy Codes .[1] The process of finding and/or using such a code is called Huffman coding and is a common technique in entropy encoding, including in lossless data compression. The algorithm s output can be viewed as a variable-length code table for encoding a source symbol (such as a character in a file). Huffman s algorithm derives this table based on the estimated probability or frequency of occurrence (weight) for each possible value of the source symbol. Platform: |
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Author:stoulod |
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Description: 熵编码(entropy encoding)是一类利用数据的统计信息进行压缩的无语义数据流之无损编码。本章先介绍熵的基本概念，然后介绍香农-范诺(Shannon-Fano)编码、哈夫曼(Huffman)编码、算术编码(arithmetic coding)、行程编码(RLE)和LZW编码等常用的熵编码方法。-Entropy coding (entropy encoding) is a kind of the compressed by using the data statistics of the semantic data flow lossless coding.This chapter first introduce the basic concept of entropy, then introduce Shannon- he (Shannon- Fano) coding, Huffman (Huffman coding, arithmetic coding, arithmetic coding), run length encoding (RLE) and entropy coding methods such as LZW encoding. Platform: |
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Author:widy |
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Description: Arithmetic coding differs other forms of entropy encoding- Arithmetic coding differs other forms of entropy encoding Platform: |
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Author:kumar |
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Description: Context-adaptive binary arithmetic coding (CABAC) is a form of entropy encoding used in the H.264/MPEG-4 AVC and High Efficiency Video Coding (HEVC) standards. It is a lossless compression technique, although the video coding standards in which it is used are typically for lossy compression applications. CABAC is notable for providing much better compression than most other entropy encoding algorithms used in video encoding, and it is one of the key elements that provides the H.264/AVC encoding scheme with better compression capability than its predecessors. Platform: |
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Author:rezajava
|
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