Decoding Algorithms by Reducing Iterations Based on Convergence Criterion

Abstract

This paper proposes a fast fractal decoding algorithm for the reconstruction of the compressed image. Its continuation of the decoding process is judged according to an image convergence criterion. Speeding up convergence of the decoding algorithm is an important research branch of fractal coding. A selective decoding excludes the converged range blocks by measuring a block convergence criterion of the range block. Double-buffer mechanism is commonly used in nowadays decoding algorithm. However, it is shown in this paper that a single-buffer algorithm is much more advisable in terms of computation and memory saving, and accelerates the convergence speed by one time approximately. Without less of quality, the reconstructed image is obtained by computation corresponding to nearly three iterations of conventional decoding.