30 Deciles-Based Accelerating Scheme for Fractal Image Encoding

Although fractal image coding has excellent visual quality at high compression ratio, it has not been widely applied due to exhaustive inherent encoding time. The time is mostly spent on find the best-matched block to every range in a usually large domain pool. To speed up fractal encoding, a fast encoding scheme is proposed, by newly defined deciles feature of normalized block, and a new theorem presented in this paper. Based on this theorem, the most inappropriate domain blocks, whose deciles features are not similar to that of the given range block, are excluded before matching. In detail, it can effectively confine the size of the search window to the vicinity of the initial-matched block (i.e., the domain block having the closest deciles feature to the input range block being encoded). Besides, an error threshold is also used to control the size of search window automatically. Simulation results demonstrate that, for three standard test images, the proposed scheme averagely obtain the speedup of 39 times or so by error threshold set 10, while can accomplish good quality of the reconstructed images against the full search method. Moreover, its performance is better than the newly cross trace feature of normalized block algorithm.