استخدام الخوارزميات الجينية المتوازية لكبس الصور الكسوري

Abstract

Efficient technologies have been recently used in fractal image
coding (FIC) to reduce the complexity of searching for matching
between range block and domain block.
The research aims at using the Parallel Genetic Algorithm (PGA)
by the technology of the (Manager/Worker) in parallel computers to
obtain matched domain blocks that prevent unsuitable convergence by
coding the site of the searching domain block with a Gray code and a
fitness function that minimizes the space between the matching of the
current range block with the domain block under discussion in order to
choose a protection strategy and coding of high accuracy for any image.
Results showed that PGA is successful in fractal image coding and
is flexible and efficient in reaching the optimum solution in higher speed
and efficiency through using the Gray code.
The searching method used for the parallel algorithm for
compression and decompression, the method of choosing GA's
coefficients, the selection, the crossover and mutation had a significant
role in improving the image compression ratio and quality. Compression
ratio has reached 87% while the image quality was improved after
decompression that reached roughly 33% compared to traditional method
in fractal image coding (FIC).