Wavelet-based fractal transforms for image coding with no search
The compression performance of fractal image coding is considered using the wavelet-based fractal coder with no search or classification of the domain blocks. A new partitioning scheme is introduced as a variant of earlier schemes which further improves the compression performance. The wavelet-based fractal transform (WBFT) links the theory of multiresolution analysis (MRA) with iterated function systems (IFS). This not only provides a local time-frequency analysis on (the partitions of) the image using multiresolution representation but also an iterative construction of the same (partitions of the) image using IFS and fixed point theory. A set of experiments and simulations show the potentials of using the WBFT for image coding after uniform quantization and entropy coding of the coefficients of the transform. Possibilities for further improvements are discussed.