Fast fractal coding of subbands using a non-iterative block clustering

Abstract

We propose a new image coding scheme which uses a fast non-iterative algorithm for block clustering in fractal coding of wavelet transform coefficients. The original image is first decomposed into subbands containing information in different spatial directions and different scales, using an orthogonal wavelet filter bank. Subbands are encoded using local iterated function systems (LIFS) with range and domain blocks presenting horizontal or vertical directionalities. Their sizes are adapted to the correlation lengths and the resolution of each subband. This hybrid compression scheme allows to use the natural classification obtained by using a subband decomposition and reduce the computational complexity by a 12:1 factor. In order to increase this speedup, we propose a fast non-iterative algorithm for block clustering which classifies the directional domain and range blocks and leads to an accelerated LIFS generation in each subband. The proposed approach reduces the computational complexity of the basic fractal compression algorithm by a 50:1 factor and gives better PSNR/bit rate results, especially for images presenting directionalities.