Fractal Compression of Images with Projected Ifs

Standard fractal image compression, proposed by Jacquin[1], is based on IFS (Iterated Function Systems) defined in R. This modelization implies restrictions in the set of images being able to be compressed. These images have to be self similar in R. We propose a new model, the projected IFS, to approximate and code grey level images. This model has the ability to define affine IFS in a high dimension space, and to project it through control points, resulting in a non strictly self similar object in R. We proposed a method for approximating curves with such a model [2, 3]. In this paper, we extend the model capabilities to surfaces and images. This includes the combination of projected IFS in a quadtree structure and a complete coding scheme. First results show that our method gives better results than standard fractal image compression. Furthermore, in the very low bitrate context, the distortion/rate performances are equivalent to those obtained with EZW algorithm.