An improved algorithm based on ROMP for compressive sensing

Abstract

The implementation of reconstruction algorithm is the core content of Compressive Sensing (CS). To improve the performance of the reconstructed signal and reduce the computational complexity, and get optimization of greedy matching pursuit algorithm, in this paper, an improved algorithm called Maximum Correlation Coefficient Regularized Orthogonal Matching Pursuit (MCC-ROMP) is proposed based on Regularized Orthogonal Matching Pursuit (ROMP) algorithm. We modified the regularization procedure of ROMP through choose the maximum correlation coefficient of the atoms located in the group J0. Numerical experiments are provided to verify that MCC-ROMP algorithm not only reduces the running time but also offers better performance of signal reconstruction.