A Fast and Low Resource Overhead Improved lzo Compression Method

Abstract

Disclosed is a fast improved LZO compression method with low resource expense. The method comprises the steps that firstly, a first compression format for compressing new characters and a corresponding first compression algorithm, a second compression format for compressing the new characters and a corresponding second compression algorithm in the LZO compression method are constructed according to anaphora distance; secondly, the length of the new characters subjected to LZO compression is recorded, and LZO compression is conducted according to the length of the new characters, the compression formats selected on the basis of the anaphora distance and the corresponding compression algorithms. According to the method, on the basis of the LZO algorithms, bit files are subjected to statistical analysis, a set of new compression formats are put forward on the premise of maintaining hash operations, a few of compression format types are divided, the judgment mode is simple, the anaphora distance is reduced on the premise of almost not reducing the compression rate, the compression and decompression speeds are both greatly increased, and the method is more beneficial to hardware implementation and aerospace application and has very good use value.

Description

technical field [0001] The invention relates to the technical field of bit file compression, in particular to an improved LZO compression method with fast speed and low resource overhead. Background technique [0002] The LZO algorithm is based on the traditional dictionary compression algorithm. It uses a hash table to record the dictionary data in the sliding window, which reduces the time to search for the same character and greatly improves the compression speed of the algorithm. It refines the compression format to use per bit , which can make full use of each byte and increase the compression ratio of data. In 2004, NASA applied LZO lossless compression to the Opportunity and Spirit rovers exploring Mars. [0003] Such as figure 1 Shown is the flow chart of the existing LZO compression algorithm, which first performs a hash operation on the input data to determine whether the input data is in the hash table, if the input data is not in the hash table, expand the hash...

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Problems solved by technology

[0005] like figure 2 The five compression formats shown can support a maximum anaphora distance of 48k, so at least 48k of decompressed data must be stored to ensure that the compressed data is decompressed correctly. Excessive RAM depth will slow down the decompression rate, and the RAM itself is decompressing When the refresh rate is reduced, in the space radiation environment, single event flipping is more likely to occur

The above 5 formats are jointly determined by anaphora distance and repetition length, which makes the determination process cumbersome and reduces the compression speed; the decompression circuit needs to distinguish the 5 compression formats, which requires a large number of control signals to ensure the correctness of decompression, making the decompression process complicated. Increased timing overhead and hardware resource overhead

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