Sorted Random Matrix for Orthogonal Matching Pursuit

Orthogonal Matching Pursuit (OMP) algorithm is widely applied to compressive sensing (CS) image signal recovery because of its low computation complexity and its ease of implementation. However, OMP usually needs more measurements than some other recovery algorithms in order to achieve equal-quality reconstructions. This article firstly illustrates the fundamental idea of OMP and the specific algorithm steps. And then, two limitations leading to the previous issue are addressed. Finally, a sorted random matrix is proposed to be used as a measurement matrix to improve those two limitations. The experimental results show the proposed measurement matrix is able to help OMP make a great progress on the quality of recovered approximations.