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Data lossless compression method based on multi-layer hash structure and run-length coding

A run-length encoding and data lossless technology, which is applied in the direction of electrical digital data processing, special data processing applications, code conversion, etc., can solve the problems of poor data compression effect and low compression rate, and achieve the elimination of poor compression effect and improve the coding efficiency. efficiency effect

Active Publication Date: 2016-04-27
HENAN ZHONGYUGUANGHENG TECH DEV CO LTD
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AI Technical Summary

Problems solved by technology

[0006] Although LZO has the advantage of fast compression, its compression rate is lower than that of lossless compression methods such as Huffman due to its inherent characteristics, especially for data with a lot of repetitive content.

Method used

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  • Data lossless compression method based on multi-layer hash structure and run-length coding
  • Data lossless compression method based on multi-layer hash structure and run-length coding
  • Data lossless compression method based on multi-layer hash structure and run-length coding

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Embodiment Construction

[0022] refer to figure 1 , the implementation steps of the present invention are as follows:

[0023] Step 1: Initialization: read in the original data, and preprocess it with the run-length encoding method, that is, encode the repeated character strings in the original data into the format of repeated characters plus repeated length. For example: the character string aaaaaa is encoded as a(06) by the run-length encoding method; the character string ccccc is encoded as c(05). After run-length encoding preprocessing, the data to be compressed is obtained.

[0024] Step 2: Initialize the reading position as the first character position in the data to be compressed, initialize the hash table as an empty table, and set the reading rule as: read four characters from the data to be compressed each time, and read After fetching, the reading position moves back four characters.

[0025] Step 3: Distinguish between the new character and the matching character, and if it is a matchin...

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Abstract

The invention discloses a multilayer Hash structure and run coding-based lossless compression method for data and mainly aims to solve the problems that a compression effect on repeating data is poor and the longest matching character string is hard to find out when matching character strings are searched by adopting a Lempel-Ziv-Oberhumer (LZO) compression method. The multilayer Hash structure and run coding-based lossless compression method for the data comprises the following implementation steps of: (1) reading in original data, and preprocessing the original data by using run coding to obtain to-be-compressed data; (2) judging the read data is a new character or not; searching the longest matching character string if the read data is not the new character, and coding according to the repeated length and the anaphora distance of the character, and coding according to a coding method for the new character if the read data is the new character; and (3) updating a reading position according to the coded character, and judging whether the end of the to-be-compressed data is coded or not, ending if the end of the to-be-compressed data is coded, and continuously reading in the to-be-compressed data if the end of the to-be-compressed data is not coded, and returning to the step (2). Compared with other traditional lossless compression methods, the multilayer Hash structure and run coding-based lossless compression method for the data is higher in compression efficiency, and can be used in storage devices with requirements on the compression speed and the compression efficiency of the data.

Description

technical field [0001] The invention belongs to the technical field of data lossless compression, relates to the compression of common data such as images, texts and programs, and can be used in storage devices that require both data compression speed and compression efficiency. Background technique [0002] With the rapid development of information technology, people's demand for data storage is increasing. In addition, the vigorous development of the network makes the data flow on the transmission channel more and more, but the bandwidth cannot bear such a huge amount of data. In order to solve the above problems, the data must first be compressed and coded to reduce the size of the original data, thereby saving the space used for data storage and increasing the speed of data transmission. [0003] At present, there are many data lossless compression methods, which can be divided into two categories: statistical-based lossless compression methods and dictionary-based lossl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H03M7/30G06F17/30
Inventor 宋彬郭洁宋秉玺秦浩胡衬
Owner HENAN ZHONGYUGUANGHENG TECH DEV CO LTD
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