Stochastic image compression using fractals

Fractal objects like the Sierpinski triangle and Fern have very high visual complexity and low storage-information content. For generating computer graphic images and compression of such objects, iterated function systems (IFS) (Barnsley; Jacquin (1992)) are used. The main problem in fractal encoding using IFS is the large amount of time taken for the compression of the fractal object. Our endeavor in the present paper is to use a stochastic algorithm to improve upon the compression time as well as compression ratio obtained in Jacquin, while maintaining the image quality. Our results show that we are able to reduce time taken for compression of images by 55%-80% and the size by 60%-80% as compared to the nonstochastic algorithm.