Optimal fractal image coding

Image compression techniques based on fractals or the iterated function systems (IFS) theory have been developed in the last few years, and may promise better compression performance. Fractal image compression techniques are being developed due to the recognition that fractals can describe natural scenes better than shapes of traditional geometry. These facts are reasoned that because images of the real world tend to consist of many complex patterns that recur at various sizes, i.e. fractals. There should be a way to translate pictures into fractal equations. Images so coded would require less data and thus less disk space to store and less time to transmit. In addition, the images are resolution-independent. In the present report, we discuss an optimal fractal image coding minimizing the Lagrangian cost function J(partition)=Distortion(partition)+/spl lambda/Rate(partition).