关键词: 压缩感知, 图像重构, 正则化正交匹配追踪, 稀疏表示

Abstract: The unsuitable iterative number of the Regularized Orthogonal Matching Pursuit (ROMP) algorithm in the framework of Compressive Sensing (CS) may reduce the quality of image reconstruction greatly. In this paper, an algorithm was proposed to determine the proper iterative number. In order to guarantee the quality of image reconstruction, the best iterative number of every image block with various sparsity was obtained by using the prior knowledge which resulted from last iteration. The experimental results show that the method can get better reconstruction performance than the ROMP algorithm with deterministic iterative number.

Key words: Compressive Sensing (CS), image construction, Regularized Orthogonal Matching Pursuit (ROMP), sparse representation