Fast fractal image encoding algorithm based on three-mean feature
三均值特征的快速分形图像编码算法

Fractal image coding has been attracting extensive attention in image compression field on account that it can provide a highly reconstructed image with a high compression ratio. Whereas it is hardly useful in many applications due to the fatal drawback of being quite time consuming during its encoding process. In response to this problem, the fast scheme is proposed to limit search space on the basis of an inequality linking the root-mean-square and newly-defined three-mean features of normalized block. It can effectively confine the searching scope of best-matched block for an input range block to the neighbourhood of the initial-matched block(i.e., the domain block having the closest three-mean features to the input range block being encoded), and the proposed algorithm sets up a predetermined kick-out condition, which is also used to control the size of search neighbourhood automatically. Simulation test results demonstrate that, for three standard test images, the proposed scheme averagely obtain the speedup of 29 times or so, while can achieve good quality for the reconstructed images against the full search method. Besides, its performance is better than newly cross trace feature of normalised block algorithm.