基于平方加权质心特征的快速分形图像压缩编码

分形图像压缩利用自身图像具有的相似性，结合压缩仿射变换减少图像数据的冗余来实现图像数据的压缩，具有压缩比高、恢复简单的特点。然而，分形图像压缩编码也具有编码时间长、计算复杂的缺点。为了解决上述的缺点，提出了基于平方加权质心特征的快速分形图像压缩编码算法，利用平方加权质心特征可以将基本分形图像压缩编码过程中的全局搜索转化为局部搜索，限定搜索范围，减少码本数量，在巨大图像信息量传输和存储过程中，在一定程度上缩短了编码时间。将平方加权质心特征快速分形图像压缩编码算法和双交叉和算法、改进叉迹算法、规范五点和算法进行比较，仿真结果表明，所提算法在恢复质量可接受情况下，编码时间具有巨大优势。

Fast Fractal Image Compression Coding Based on Square Weighted Centroid Feature

Fractal image compression utilizes the similarity of its own image,and uses compression affine transformation to reduce the redundancy of image data to achieve image data compression.It has the characteristics of high compression ratio and simple recovery.However,fractal image compression coding has the disadvantages of long coding time and complicated calculation.In order to solve the above shortcomings,a fast image compression coding algorithm based on square-weighted centroid feature is proposed.The squared-weighted centroid feature can be used to convert the global search in the basic fractal image compression coding process into local search,which limits the search range and reduces the number of codebooks.In the process of huge image information transmission and storage,the coding time is shortened to some extent.The squared-weighted centroid feature fast fractal image compression coding algorithm is compared with the double cross sum algorithm and the improved crossover algorithm and the norm five point sum algorithm.When the recovery quality is acceptable,the simulation results show that the proposed algorithm has great advantages in coding time.