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Application of Learning Automata to Image Data Compression

In: Adaptive and Learning Systems

Author

Listed:
  • A. A. Hashim

    (Leicester Polytechnic)

  • S. Amir

    (Leicester Polytechnic)

  • P. Mars

    (Leicester Polytechnic)

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.

Suggested Citation

  • A. A. Hashim & S. Amir & P. Mars, 1986. "Application of Learning Automata to Image Data Compression," Springer Books, in: Kumpati S. Narendra (ed.), Adaptive and Learning Systems, pages 229-234, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-1895-9_15
    DOI: 10.1007/978-1-4757-1895-9_15
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