Block Compressed Sensing Image Reconstruction Based on SL0 Algorithm

Juan Zhao*, Xia Bai, Jieqiong Xiao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

By applying smoothed l0 norm (SL0) algorithm, a block compressive sensing (BCS) algorithm called BCS-SL0 is proposed, which deploys SL0 and smoothing filter for image reconstruction. Furthermore, BCS-ReSL0 algorithm is developed to use regularized SL0 (ReSL0) in a reconstruction process to deal with noisy situations. The study shows that the proposed BCS-SL0 takes less execution time than the classical BCS with smoothed projected Landweber (BCS-SPL) algorithm in low measurement ratio, while achieving comparable reconstruction quality, and improving the blocking artifacts especially. The experiment results also verify that the reconstruction performance of BCS-ReSL0 is better than that of the BCS-SPL in terms of noise tolerance at low measurement ratio.

Original languageEnglish
Pages (from-to)357-366
Number of pages10
JournalJournal of Beijing Institute of Technology (English Edition)
Volume26
Issue number3
DOIs
Publication statusPublished - 1 Sept 2017

Keywords

  • Block
  • Compressed sensing (CS)
  • Smoothed l norm (SL0)

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