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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2017> 26(3): 357-366
Juan Zhao, Xia Bai. Block Compressed Sensing Image Reconstruction Based on SL0 Algorithm[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2017, 26(3): 357-366. doi: 10.15918/j.jbit1004-0579.201726.0311
Citation: Juan Zhao, Xia Bai. Block Compressed Sensing Image Reconstruction Based on SL0 Algorithm[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2017, 26(3): 357-366.doi:10.15918/j.jbit1004-0579.201726.0311
shu

Block Compressed Sensing Image Reconstruction Based on SL0 Algorithm

doi:10.15918/j.jbit1004-0579.201726.0311

  • School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China;Beijing Key Laboratory of Fractional Signals and Systems, Beijing 100081, China

  • Received Date:2016-12-01
    Abstract
  • By applying smoothed l 0norm (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.
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