Data compression method based on set run

Abstract

The invention discloses a data compression method based on the set run, including reading the data to be compressed in the memorizer of the computer; looking for the characteristic character set in the data; coding; storing the compressed data into the memorizer of the computer. Looking for the characteristic character set in the data includes the following steps: counting the isolated character; judging whether presenting the isolated character, if true, executing the next step, else converting all the characters into the characteristic characters, wherein the continuous occurrence number mapped by each character is the numerical value, and converting to the coding step; sorting the isolated character; traversing the number of each element that may occur of all the characteristic character set, selecting the number of the characteristic character set when the compression ratio reach the minimum; mapping each element in the characteristic character set till the element appears continuously. The invention advances the efficiency of the run length coding, and obtains better data compression effect in the computer data compression process.

Description

technical field [0001] The invention relates to a data compression method in the computer field, in particular to a set-run-based data compression method with good compression ratio. Background technique [0002] With the rapid development of computer technology and information technology, a large amount of information is represented, stored and transmitted in a digital way, such as radar, image, voice, etc. An important problem facing today is that this information occupies a huge space , taking the radar signal as an example, a radar trigger has 3000 pixels, and it takes 15 seconds to scan one week (including 4096 triggers), and its data rate needs to be 6.3Mbps. It takes 12M bytes to save a radar image, and the amount of data is very large. of. Similarly, a large amount of data also brings inconvenience to analysis and transmission, and puts great pressure on communication. Compared with increasing the capacity of storage devices and increasing communication bandwidth, t...

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Problems solved by technology

[0006] However, the above improvement does not solve the following problems: 1. If a large number of isolated characters in a certain data appear greater than C0, there will inevitably be a "morbid" situation, so that the data after compression is twice the data before compression

2. The above encoding can only express a maximum of 63 consecutive identical bytes, which cannot be adjusted, which limits the improvement of compression efficiency

3. The fixed threshold C0 limits the compression effect, and does not make corresponding adjustments according to the characteristics of the data type

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