Block-sparse signal recovery based on orthogonal matching pursuit via stage-wise weak selection

• Published in: Signal, image and video processing Vol. 14; no. 1; pp. 97 - 105
• Main Authors: Xia, C. Y., Gao, Y. X., Yu, J., Yu, ZH
• Format: Journal Article
• Language: English
• Published: London Springer London 01.02.2020; Springer Nature B.V
• Subjects: Algorithms; Computer Imaging; Computer Science; Computer simulation; Image Processing and Computer Vision; Matched pursuit; Matching; Multimedia Information Systems; Original Paper; Pattern Recognition and Graphics; Recovery; Signal reconstruction; Signal,Image and Speech Processing; Vision; RIP; Block-sparse; Compressing sensing; BOMP
• ISSN: 1863-1703; 1863-1711
• DOI: 10.1007/s11760-019-01529-x

For recovering the block-sparse signal with unknown block structures, this paper presents a Block Stage-wise Weak Orthogonal Matching Pursuit (BSWOMP) algorithm. Which partitions the original signal into different groups or segments and conducts the selection for these groups separately using weak selection method to update reconstructing support set. And it proves that the Restricted Isometry Property (RIP) of BSWOMP algorithm is slack than Stage-wise Weak Orthogonal Matching Pursuit (SWOMP) algorithm and Block Orthogonal Matching Pursuit (BOMP) algorithm, this means BSWOMP algorithm generates better convergence than traditional sparse signal recovery algorithm. To further analysis of the performance of BSWOMP, the effectiveness of this algorithm is demonstrated by simulations. Experiments results show that the proposed algorithm effectively selects the nonzero elements of the block-sparse signal by a threshold, and compared with the traditional algorithms, BSWOMP algorithm has higher recovering stability, expedites the approximate conjugate gradient update step and brings an evident performance improvement and application prospect.