Genetic fractal image compression
A. Gafour, Kamel Mohamed Faraoun, Ahmed Lehireche
Abstract
A. Gafour, Kamel Mohamed Faraoun, Ahmed Lehireche
Abstract
Summary form only given. The fractal image compression problem put forward three major requirements: speeding up the compression algorithm, improving image quality or increasing compression ratio. Major variants of the standard algorithm were proposed to speed up computation time. But most of them lead to a bad image quality, or a lower compression ratio. We present an implementation based on genetic algorithms. The main goal is to accelerate image compression without significant loss of image quality and with an acceptable compression rate. Results prove that genetic compression is a good choice.
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Summary form only given. The fractal image compression problem put forward three major requirements: speeding up the compression algorithm, improving image quality or increasing compression ratio. Major variants of the standard algorithm were proposed to speed up computation time. But most of them lead to a bad image quality, or a lower compression ratio. We present an implementation based on genetic algorithms. The main goal is to accelerate image compression without significant loss of image quality and with an acceptable compression rate. Results prove that genetic compression is a good choice.
Key concepts: Fractal compression, Fractal transform, Image compression, Texture compression, Data compression ratio, Computer science, Data compression, Compression (physics)