基于稀疏分解的分块图像压缩编码算法

Block Compressed Image Coding Based on Sparse Decomposition

以压缩感知理论为基础,将匹配追踪(Matching Pursuit,简称MP)算法运用到图像的压缩编码中.首先,阐述了原子库的构建方法,之后,采用分块感知压缩图像分解方法,降低了分解的运算复杂度,最后,针对传统MP算法编码率不高的问题,利用MP原子能量与位置分布特点,对原子系数和位置参数进行编码,并提出了MP原子编码方法.实验结果表明,采用分块感知压缩图像分解方法,能有效地降低稀疏分解的计算复杂度,其压缩编码方法在保持传统MP图像编码优势的前提下,能有效地提高编码性能和编码率,体现了稀疏分解较传统分解方法的优势.

Based on the compressed sensing theory, the MP （Matching Pursuit, MP） algorithm was applied to image compression coding. This paper presented the reconstructed method of the atomic library and reduced the computational complexity of the traditional MP decomposition by using the decomposition method of the block compressed sensing image. Aiming at the low coding rate problem of the traditional MP algorithm, a coding method of MP atoms was proposed, and the coefficient of the atomic and position- al parameters was encoded by using MP atomic energy and position distribution characteristics. The exper- iment results have shown that： 1）the decomposition method of the block compressed sensing image can ef- fectively reduce the computational complexity of sparse decomposition; 2）that the compression coding method, besides maintaining the strengths of the traditional MP image coding, can effectively improve the coding performance and the encoding rate, and reflect the advantage of the sparse decomposition over the traditional decomposition methods.