One of the main drawbacks of fractal im-age coding (FIC) is its time-consuming encoding process. So how to speed up the encoding process is a challenging issue of FIC research. As both sequential solutions and parallel ones have their advantages and disadvantages, we combine them together to further speed up the encoding phase. In this paper a derivative tree topology is first pro-posed to provide support for complex parallelism. Then a dual-classification technique is designed for speeding up the fractal image coding with Same-Sized Block Mapping, which improves the decoded image quality. Finally, some experimental results with good performance are presented.

The fractal image coding technique has attracted a degree of interest for its low bit rate. But the reconstructed image is of medium quality. This problem has prevented the fractal technique from being practically used. In order to improve the compression fidelity, a new affine ransformation is roposed in this paper. Meanwhile, its contractivity requirement is analyzed, and the optimal parameters are derived using the least square method. The new affine transformation has been practically used in image coding. Experiments show that the PSNR can reach 28.7dB at a compression ratio (CR) of 16.4 for the 256 256 8 "Lena" image. Comparison with other fractal coding schemes shows that the new affine transformation can improve the reconstructed image quality efficiently.