Wavelet-based fractal image compression

In this paper, a wavelet-based fractal image coding algorithm is proposed. The conventional fractal image coding in spatial domain is extended to wavelet domain by taking advantage of the self-similarities among different wavelet subtrees through proper affine transformation.. This method is based on the combination of the theory of multi-resolution analysis with iterated function systems by introducing some effective block-classification schemes. The original image is first transformed into wavelet domain in which fractal compression and arithmetic coding are performed. By classifying D blocks and R blocks set in this domain, the approach can significantly reduce the computation complexity and encoding time. Meanwhile, the hybrid image compression algorithm obtains much better coding performance in terms of PSNR with error modification. This is the main advantage of this method. A set of experiments and simulations show the potentials of using these classification techniques in wavelet domain for further improvements.