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Fractal image compression based on spatial correlation and hybrid genetic algorithm

Authors
Journal
Journal of Visual Communication and Image Representation
1047-3203
Publisher
Elsevier
Publication Date
Volume
20
Issue
8
Identifiers
DOI: 10.1016/j.jvcir.2009.07.002
Keywords
  • Fractal Image Compression
  • Block Coding
  • Pifs
  • Spatial Correlation
  • Hybrid Genetic Algorithm
  • Simulated Annealing
  • Neighborhood
  • Dyadic Mutation Operator
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract In order to solve the high complexity of the conventional encoding scheme for fractal image compression, a spatial correlation hybrid genetic algorithm based on the characteristics of fractal and partitioned iterated function system (PIFS) is proposed in this paper. There are two stages for the algorithm: (1) Make use of spatial correlation in images for both range and domain pool to exploit local optima. (2) Adopt simulated annealing genetic algorithm (SAGA) to explore the global optima if the local optima are not satisfied. In order to avoid premature convergence, the algorithm adopt dyadic mutation operator to take place of the traditional one. Experiment results show that the algorithm convergent rapidly. At the premise of good quality of the reconstructed image, the algorithm saved the encoding time and obtained high compression ratio.

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