Fractal coding versus classified transform coding

Fractal coding and classi ed transform coding exhibit strong structural similarity, but they use di erent types of redundancy in image data: piecewise self-similarity in one case and local correlation in the other. Comparing performance of the two techniques leads to a quantitative, compression-oriented de nition of piecewise self-similarity. The amount of piecewise self-similarity is evaluated for sample images. For a moderate number of domain blocks, classi ed transform coding consistently outperforms fractal coding, and the images are not found to be piecewise self-similar. As the number of domain blocks increases, the performance gap becomes negligible.