Application of Learning Automata to Image Data Compression

  • A. A. Hashim
  • S. Amir
  • P. Mars

Abstract

A novel approach to image data compression is proposed which uses a stochastic learning automaton to predict the conditional probability distribution of the adjacent pixels. These conditional probabilities are used to code the gray level values using a Huffman coder. The system achieves a 4/1.7 compression ratio. This performance is achieved without any degradation to the received image.

Keywords

Compression Ratio Image Code Conditional Probability Distribution Learning Automaton Huffman Coder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1986

Authors and Affiliations

  • A. A. Hashim
    • 1
  • S. Amir
    • 1
  • P. Mars
    • 1
  1. 1.Leicester PolytechnicUK

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