Data compression method, data compression system, data decompression method and data decompression system

Abstract

The invention discloses a data compression method based on Huffman coding, comprising the following steps of selecting target data from original data; by means of a dynamic Huffman coding algorithm, generating a local dynamic coding table corresponding to each character of the target data; detecting whether to-be-coded characters in the original data are located in the local dynamic coding table; if so, coding the characters through the local dynamic coding table; if not, coding the characters through a fixed coding table; and storing a data file formed after coding and the local dynamic coding table together as a compressed file of the original data. Obviously, as compared with static Huffman coding, the scheme provided by the invention has better compression ratio; and as compared with the conventional dynamic Huffman coding, the scheme provided by the invention has faster compression speed and lower coding table storage overhead. The invention also provides a data compression system, a data decompression method and a data decompression system based on the Huffman coding, which also can achieve the above technical effects.

Description

technical field [0001] The present invention relates to the technical field of data compression, and more specifically, to a data compression method and system, and a decompression method and system. Background technique [0002] Huffman coding is a consistent coding method (also known as "entropy coding method") for lossless compression of data. It establishes a code table according to the probability of each character. Characters with a high probability of occurrence use a shorter code, whereas characters with a low probability of occurrence use a longer code, so that the average expected length of the coded string is reduced, so as to achieve The purpose of losslessly compressing data. [0003] The implementation of Huffman coding is divided into static Huffman coding and dynamic Huffman coding. Static Huffman coding uses a predefined fixed code table for coding, and does not need to save the code table information, but because the code table is fixed, it is not necessa...

AI Technical Summary

Problems solved by technology

But there are the following defects: 1) need to scan the file to be compressed before encoding to obtain the frequency of character appearance, this process is time-consuming, especially for large files, the compression time is longer; 2) need to transmit additional code table information, when compressed When the data is relatively small or special data is encountered, the length of the output content of dynamic Huffman encoding will be longer than that of static Huffman encoding, and in extreme cases it may be longer than the length of uncompressed original data content

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