A Genetic-Algorithm Based Quantization Method for Fractal Image Coding

Megumi Takezawa, Hiroyuki Honda, Junichi Miura, Miki Haseyama, Hideo Kitajima

Abstract: This paper proposes a high-accuracy quantization method for IFS parameters in fractal image coding by using a genetic algorithm (GA). The development of IFS-parameter quantization techniques is significant for the image coding because its errors make more serious problems in the iteration procedures than the other quantization topics. Even if the errors are small, high-quality reconstructed images are not necessarily obtained. Therefore, the high-accuracy quantization methods are required for the parameters. The proposed method provides higher quality reconstructed images than a conventional method which merely minimizes the errors.