On the reconstruction of sequences of sparse signals - The Weighted-CS

  • Authors:
  • Dornoosh Zonoobi;Ashraf A. Kassim

  • Affiliations:
  • Department of Electrical and Computer Engineering, National University of Singapore, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Singapore

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2013

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Abstract

In this paper, we study the problem of recursively reconstructing time sequences of sparse signals, where sparsity changes smoothly with time. The idea is to use the signal/image of the previous time instance to extract an estimated probability model for the signal/image of interest, and then use this model to guide the reconstruction process. We examine and illustrate the performance of our approach, ''Weighted-CS'', with both synthetic and real medical signals/images. It is shown that we can achieve significant performance improvement, using fewer number of samples, compared to other state-of-art Compressive Sensing methods.