出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Traditional methods to signal acquisition need to collect large amounts of redundant data, andthen compress the data to extract useful information, which is inefficient and requires largeamount of storage resources. Compressed sensing (CS) can avoid sampling the redundant data;it obtains the discrete signals at the sampling rate that is lower than the Nyquist sampling rate,and reconstructs the original signal with high probability. Based on CS, Block StagewiseRegularized Orthogonal Matching Pursuit (StROMP) is proposed in this paper to reconstructimages. Simulation results show that the proposed algorithm can effectively reduce the requiredstorage storages and computational complexity, which improves the quality of reconstructedimages in the premise of ensuring a shorter reconstruction time.
