Implementation of Genetic Algorithm with Ranking Select Mechanism for Fractal Image Compression

The immense use of the images in the field of communication and animation drives the attention towards an important concept i.e. compression, because of compactness and restricted size for the data storage. From last few years a continuous development is going on in the field of compression. For still image compression JPEG is used world -wide. But other methods are also being explored; Fractal image compression is another major tool accepted for the same. It has the base of selfsimilarity property using which the best match image block is found out. Traditional method of FIC involves lot of computations resulting into a large encoding time for the entire image to develop the fractal code. In this paper, the new approach for fractal image compression using genetic algorithm with ranking select mechanism is proposed. This proposed algorithm is applied on fractal as well as non-fractal images. The use of genetic algorithm emphasize only on the encoding time and the experimental test result shows that the encoding time for both types of images is greatly reduced while other parameters such as PSNR, Compression ratio are not hampered. KeywordsFractal, PSNR, Genetic Algorithm, Ranking select mechanism, MSE