Application of Learning Automata to Image Data Compression

A. A. Hashim, S. Amir and P. Mars
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A. A. Hashim: Leicester Polytechnic
S. Amir: Leicester Polytechnic
P. Mars: Leicester Polytechnic

A chapter in Adaptive and Learning Systems, 1986, pp 229-234 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 1986
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DOI: 10.1007/978-1-4757-1895-9_15

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