Huffman coding method, system and device and readable storage medium

Abstract

The invention discloses a Huffman coding method, a Huffman coding system, a Huffman coding device and a readable storage medium. The method comprises the following steps: acquiring a target data block in a target file; performing frequency distribution statistics on the target data block to obtain a first frequency distribution result; obtaining a second frequency distribution result by using the first frequency distribution result and a frequency distribution result of a preset data block in the target file; constructing a first Huffman tree by using the first frequency distribution result; judging whether the depth of the first Huffman tree exceeds a preset value or not; if not, coding the target data block by using the first Huffman tree; and if yes, constructing a second Huffman tree by using the second frequency distribution result, and encoding the target data block by using the second Huffman tree. According to the method, when the depth of the first Huffman tree exceeds the preset value, the second frequency distribution result is selected to be generated for subsequent characterization and coding, the first Huffman tree is not traversed in the process, the effect of correcting the ultra-long code is also achieved, and the efficiency is obviously improved.

Description

technical field [0001] The invention relates to the field of data compression, in particular to a Huffman encoding method, system, device and readable storage medium. Background technique [0002] With the explosive growth of data in the field of information science, servers are under great pressure on how to store massive amounts of data. Data compression has become an effective means to reduce the storage burden of servers and reduce storage costs. Common data compression standards, such as Gzip, zip, zlib, etc., will compress and encapsulate data blocks into data in a deflate format. deflate is a lossless data compression algorithm, which uses the LZ77 algorithm to find duplicate data in the data. Fenman coding represents and encodes repetitive data. [0003] Since the Huffman tree generated by sorting during Huffman encoding may be too deep and the code may appear super long, when the maximum depth specified by the deflate protocol is exceeded, the Huffman tree exceedin...

AI Technical Summary

Problems solved by technology

This method can obtain the Huffman tree that guarantees the optimal compression rate, but the traversal search is extremely time-consuming, and it cannot be traversed in parallel in special cases. In extreme cases, the time consumption of correcting the Huffman tree may be several times that of building a Huffman tree. Time consumption of Fman tree

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