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|Title:||On the reconstruction of sequences of sparse signals - The Weighted-CS||Authors:||Zonoobi, D.
Medical image reconstruction
Weighted ℓ1 minimization
|Issue Date:||Feb-2013||Citation:||Zonoobi, D., Kassim, A.A. (2013-02). On the reconstruction of sequences of sparse signals - The Weighted-CS. Journal of Visual Communication and Image Representation 24 (2) : 196-202. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jvcir.2012.05.002||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. © 2012 Elsevier Inc. All rights reserved.||Source Title:||Journal of Visual Communication and Image Representation||URI:||http://scholarbank.nus.edu.sg/handle/10635/82819||ISSN:||10473203||DOI:||10.1016/j.jvcir.2012.05.002|
|Appears in Collections:||Staff Publications|
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