Evolutionary Fractal Image Compression Using Asexual Reproduction Optimization with Guided Mutation

There are many different methods for imagecompression which each of them satisfies a various type ofpurposes. Fractal Image Compression is a category of thesetechniques that has some specific features. This method is robustagainst aliasing of images in zooming, so it has multi-resolutioncapability. Besides, compression ratio of this method isreasonably competitive, also its decoding is fast. But the mainissue of this method is the compression time which is very highbecause of complexity for finding self-similar blocks. Soresearchers have tried to mitigate computational costs withdifferent approaches. In this paper, using an evolutionaryalgorithm called Asexual Reproduction Optimization (ARO) isproposed for fractal image compression. Then the main operatorof this algorithm is tuned to make it more efficient versus otherindividual-based algorithms like Simulated Annealing (SA) andTabu Search (TS). Finally experimental results and executiontime of the proposed method, SA and full search are compared.ARO with guided mutation generates defensible outputs in veryshort time versus the others approaches

کلیدواژه ها:

Fractal Image Compression ، Iterated Function Systems ، Asexual Reproduction Optimization ، Guided Mutation Tabu Search ، Simulated Annealing