关键词: 图像压缩, 分形, 分形图像编码, 图像子块特征

Abstract: The full search fractal image encoding algorithm is based on the partitioned iteration function system, its encoding process requires a very long run-time, which limits its practical application. By defining the sub-block features of each range block and domain block, this paper thus proposes an effective method of liming the search space to improve the drawback, which is mainly based on inequality linking the root-mean-square and image sub-block feature. During the search process, the image sub-block feature is utilized to confine efficiently the search space to the vicinity of the domain block having the closest image sub-block feature to the input range block being encoded, aiming at reducing the searching scope of similarity matching to accelerate the encoding process. Simulation results of fourteen test images show that the proposed scheme can averagely reduce the run-time by about 99 times while there is averagely the [PSNR] decrease of 0.73 dB（the structural similarity decrease of 0.002）, in comparison with the full search fractal algorithm.Moreover, it is better than the other feature algorithm.

Key words: image compression, fractal, fractal image coding, image sub-block feature