Stochastic Image Compression Using Fractals

Fractal objects like 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) {[3] , [1]} are recently being used. The main problem in fractal encoding using IFS is large amount of time taken for the compression of the fractal object. Our endeavor in the present paper is to use an stochastic algorithm to improve upon the compression time as well as compression ratio obtained in [1], while maintaining the image quality. Our results show that we are able to reduce time taken for compression of Image by 55% - 80% and the size by 60% - 80% as compared to the non-stochastic algorithm.

• Type: Conference
• Year: 2003
• Where: ITCC
• Authors: Aditya Kapoor, Kush Arora, Ajai Jain, G. P. Kapoor
• Keywords: Fractal Object, ITCC 2003, Iterated Function Systems, Low Storage-information Content