The convergence of the block cyclic projection with an overrelaxation parameter for compressed sensing based tomography

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:280

Article

Arroyo, Fangjun¹  Arroyo, Edward²  Li, Xiezhang³  Zhu, Jiehua³ 

[1] Francis Marion Univ, Dept Math, Florence, SC 29501 USA

[2] Amer Publ Univ Syst, Sch Sci Technol Engn & Math, Manassas, VA 20109 USA

[3] Georgia So Univ, Dept Math Sci, Statesboro, GA 30460 USA

关键词: Compressed sensing;    Image reconstruction;    Total variation minimization;    Amalgamated projection method;    Block iterative algorithm;   

DOI  :  10.1016/j.cam.2014.11.036

来源: Elsevier

【 摘 要 】

The convergence of the block cyclic projection for compressed sensing based tomography (BCPCS) algorithm had been proven recently in the case of underrelaxation parameter lambda is an element of (0, 1). In this paper, we prove its convergence with overrelaxation parameter lambda is an element of (1, 2). As a result, the convergence of the other two algorithms (BCAVCS and BDROPCS) with overrelaxation parameter lambda is an element of (1, 2) in a special case is derived. Experiments are given to demonstrate the convergence behavior of the BCPCS algorithm with different values of A. (C) 2014 Elsevier B.V. All rights reserved.

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