Regular Articles

Fast sparsity adaptive multipath matching pursuit for compressed sensing problems

[+] Author Affiliations
Xiaofang Zhang, Hongwei Du, Bensheng Qiu, Shanshan Chen

University of Science and Technology of China, Centers for Biomedical Engineering, Hefei, Anhui, China

J. Electron. Imaging. 26(3), 033007 (May 13, 2017). doi:10.1117/1.JEI.26.3.033007
History: Received January 26, 2017; Accepted April 26, 2017
Text Size: A A A

Abstract.  The high computational complexity of tree-based multipath search approaches makes putting them into practical use difficult. However, reselection of candidate atoms could make the search path more accurate and efficient. We propose a multipath greedy approach called fast sparsity adaptive multipath matching pursuit (fast SAMMP), which performs a sparsity adaptive tree search to find the sparsest solution with better performances. Each tree branch acquires K atoms, and fast SAMMP reselects the best K atoms among 2K atoms. Fast SAMMP adopts sparsity adaptive techniques that allow more practical applications for the algorithm. We demonstrated the reconstruction performances of the proposed fast scheme on both synthetically generated one-dimensional signals and two-dimensional images using Gaussian observation matrices. The experimental results indicate that fast SAMMP achieves less reconstruction time and a much higher exact recovery ratio compared with conventional algorithms.

Figures in this Article
© 2017 SPIE and IS&T

Citation

Xiaofang Zhang ; Hongwei Du ; Bensheng Qiu and Shanshan Chen
"Fast sparsity adaptive multipath matching pursuit for compressed sensing problems", J. Electron. Imaging. 26(3), 033007 (May 13, 2017). ; http://dx.doi.org/10.1117/1.JEI.26.3.033007


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.