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An Adaptive Multiple Order Context Huffman Compression Algorithm Based on Markov Model

  • Yonghua HuoEmail author
  • Zhihao Wang
  • Junfang Wang
  • Kaiyang Qu
  • Yang Yang
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 201)

Abstract

In this paper, an adaptive multiple order context Huffman compression algorithm based on Markov chain is proposed. Firstly, the data to be compressed is traversed, and the character space of the data and the times that one character transfers to its neighboring character are figured out. According to the statistical results, we can calculate the one-step transition probability matrix and the multi-step transition probability matrix. When the conditional probability between two adjacent characters is greater than the set threshold value, the adjacent characters are merged and compressed as an independent encoding unit. Improve the compression efficiency by increasing the length of the compression characters. The experimental results show that the algorithm achieves good compression efficiency.

Keywords

Data compression Multiple order contexts Markov chain Huffman compression 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Authors and Affiliations

  • Yonghua Huo
    • 1
    Email author
  • Zhihao Wang
    • 1
  • Junfang Wang
    • 1
  • Kaiyang Qu
    • 2
  • Yang Yang
    • 2
  1. 1.Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory54th Research Institute of China Electronics Technology Group CorporationShijiazhuangChina
  2. 2.State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

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