LZW-based lossless data compression and decompression method, and LZW encoder and decoder

Abstract

The invention relates to an LZW-based lossless data compression and decompression method, and an LZW encoder and decoder. The compression comprises the following steps: reading a character string to be compressed, decomposing the character string to be compressed into a sequence of original phrases, performing coding matching on the sequence of the original phrases and the data in a dictionary, outputting the corresponding characters according to a matching result and obtaining a compressed data stream; selecting two non-negative integers as embedded parameters K and L, dividing a preset message into successive groups of data blocks, wherein each group of data blocks comprises two sub-blocks, and each sub-block is represented by parameters k and l; and embedding the data blocks in the compressed data stream according to k and l and generating a final compressed data stream. According to the LZW-based lossless data compression and decompression method in the invention, for the LZW compressed data stream, a partially encoded codeword is selected and the length of the corresponding compressed character string is dynamically adjusted; the extra message bit is embedded by using the dynamically adjusted codeword phrase mode; under the premise without affecting the overall compression performance of the LZW algorithm, the compatibility and the practicability are strong as the coding rule and the data format are not changed.

Description

technical field [0001] The invention belongs to the technical field of data compression, and in particular relates to an LZW-based lossless data compression and decompression method, an LZW encoder and a decoder. Background technique [0002] Under the guidance of the source-channel separation theory, in the current communication system, source coding realizes the problem of communication validity, and channel coding realizes the problem of communication reliability. Due to the limitations of the separation theorem, the design idea of ​​cascade coding makes the anti-interference ability of the coded sequence of the source very weak. In fact, the lack of repair ability of adaptive data compression is a prominent shortcoming in many applications. From the analysis of the source coding mechanism, it can be seen that the data obtained by source coding is almost without redundancy. After the data is transmitted through the channel, there are often bit errors due to the influence...

AI Technical Summary

Problems solved by technology

Although these methods can achieve certain results, the complexity of the algorithm is high, and the compression performance will be reduced. More importantly, due to the modification of the encoding rules and data format, it cannot be compatible with the standard algorithm, so the practicability is compromised.

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