Fractal image compression using iterated function system with probabilities

Abstract

Deals with a new technique of fractal image compression based on the theory of iterated function systems (IFS) with probabilities. The theory of IFS with probabilities, in the context of image compression, is a relatively unexplored area. The rationale behind using this approach stems from the fact that it is possible to define a Markov operator associated with the probability measure whose support is the support of the given image. A new technique of fractal image compression is proposed using IFS with probabilities. The technique is found to be extremely fast in computing both the coefficients of maps and the probabilities. Thus, the proposed technique provides a very fast fractal-based image compression encoding.