四线和特征的快速分形图像编码

分形图像编码具有压缩比高、解码速度快、重构图像质量高等特点,但因这种算法在编码时定义域的搜索量十分巨大,导致其计算复杂度高、编码时间过长,阻碍了它的实用性和普遍应用.为解决此问题,文中提出一种基于四线和特征值编码算法,该算法根据匹配均方根误差与四线和特征间的关系,将全局搜索转化为局部搜索(近邻搜索),限定搜索空间,减少定义域块的搜索,从而提高编码速度.仿真实验结果表明:该算法解码图像质量在客观上优于1 -范数特征算法;与基本分形编码算法相比,基于四线和特征算法在主观上不改变重构图像质量,但在编码速度上却得到极大提高.

Fast Fractal Image Encoding with Sum of Four Lines Eigenvalues

Fractal image encoding has many advantages,such as high compression ratio,high decoding speed and high quality of re-constructed image.However,its high computational complexity and long encoding time make it impractical because of the huge a-mount of search in the domain.Aiming at these problems,an encoding algorithm based on the sum of four lines eigenvalues is pro-posed.And,the relationship between the matching error and the four lines eigenvalues converts global search to local search(neigh-bor search)to limit the search space and speed up the encoding.The simulation experiment results show that the objective decoding image quality by the algorithm of this paper is superior to 1 -norm features algorithm.Compared with the basic fractal coding algo-rithm,it doesn't change the subjective quality of reconstructed image but the speed of encoding has been greatly improved.