Huffman coding

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Huffman coding

(algorithm)
A data compression technique which varies the length of the encoded symbol in proportion to its information content, that is the more often a symbol or token is used, the shorter the binary string used to represent it in the compressed stream. Huffman codes can be properly decoded because they obey the prefix property, which means that no code can be a prefix of another code, and so the complete set of codes can be represented as a binary tree, known as a Huffman tree. Huffman coding was first described in a seminal paper by D.A. Huffman in 1952.

Huffman coding

A statistical compression method that converts characters into variable length bit strings. Most-frequently occurring characters are converted to shortest bit strings; least frequent, the longest. Compression takes two passes. The first pass analyzes a block of data and creates a tree model based on its contents. The second pass compresses the data via the model. Decompression decodes the variable length strings via the tree. See LZW.
References in periodicals archive ?
In the second part of this algorithm, a move-to-front strategy is applied against the result obtained in the first part, followed by a Huffman encoding.
Huffman encoding is used to convert coefficients into binary values and transmitted.
Keywords: MATLAB, Image Compression, Mean Square Error (MSR), Huffman Encoding
[9] studied the function of MAC address in WSN and proposed a variable length MAC address encoding scheme, with which traditional fixed length MAC addresses are replaced by variable length local addresses which are coded in the Huffman encoding. According to their study, the proposed scheme achieved a MAC layer overhead reduction by a factor of three.
Here, the idea is to decrease the drop of compression rate by only using the small offsets so that the Huffman encoding in the second step of ZIP/ LHA is still not disturbed too much.
RLE is best suited to graphics applications, "whereby large areas of an image are constant, but it is less effective when used with most medical images." (6) Huffman encoding (HE) is another method of lossless compression that can operate on text data as well as on images.
The JPEG encoder implements all computationally intensive tasks such as DCT encoding, RLE and Huffman encoding in hardware.
A number of papers have appeared on the subject of implementations of Huffman encoding and decoding.
The four-level compression algorithm includes a level using modified Huffman Encoding, a scheme that substitutes an eight-bit character code with a shorter code.
Therefore, we show that, if the statistics of this phenomenon are known beforehand from general datasets, and if the data collected by the sensor nodes presents relatively low resolution, by employing simple Huffman encoding, it is possible to achieve compression ratios higher than those obtained by state-of-the-art algorithms such as those presented in [2-4].
In the implementation, for entropy coding purposes the Adaptive Huffman encoding was selected.
We experimented with a fixed Huffman encoding, a hand-designed family of codewords, and a variable-length encoding of the integers, so we will compare these options briefly: