基于变异系数的分形图像压缩稀疏编码算法

针对分形图像编码算法复杂度高、编码时间冗长的问题,提出正交稀疏编码和纹理特征提取表示图像块的方法.首先,灰度级的正交稀疏变换提高了图像的重建质量和解码时间.其次,相关系数矩阵度量范围块和域块之间的变异系数特征降低了冗余度和编码时间.仿真实验结果显示,该方法与传统的分形图像编码算法相比,图像重建质量更好,编码速度更快.

Sparse coding algorithm for fractal image compression based on coefficient of variation

Aiming at the problem of high complexity and long coding time of fractal image coding algorithm, the paper proposes orthogonal sparse coding and texture feature extraction to represent image blocks. Firstly, the orthogonal sparse transformation of gray level improved the image reconstruction quality and decoding time. Secondly, the correlation coefficient matrix measured the coefficient of variation characteristics between the range block and the domain block to reduce redundancy and coding time. The simulation results show that the proposed method has better image reconstruction quality and faster coding speed than the traditional fractal image coding algorithm.