Acceleration Forward-backward Pursuit Algorithm Based on Compressed Sensing
WANG Feng① SUN Guiling① ZHANG Jianping② HE Jingfei①
①(College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China) ②(School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200030, China)
The Forward-Backward Pursuit (FBP) algorithm, a novel two stage greedy approach, receives wide attention due to the high reconstruction accuracy and the feature without prior information of the sparsity. However, FBP has to run more time to get a higher precision. To alleviate this drawback, this paper proposes the Acceleration Forward-Backward Pursuit (AFBP) algorithm based on Compressed Sensing (CS). In order to reduce the number of iterations, the algorithm exploits the information available in the support estimate to add the deleted atoms again. The run time of AFBP is sharply shorter than that of FBP, while the precision of AFBP is not lower than FBP. The efficacy of the proposed scheme is demonstrated by simulations using random sparse signals with different nonzero coefficient distributions and a sparse image.
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