| Visually Weighted Compressive Sensing: Measurement and Reconstruction. | |
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MedLine Citation:
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PMID: 23221825 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Compressive Sensing (CS) makes it possible to more naturally create compact representations of data with respect to a desired data rate. Through wavelet decomposition, smooth and piecewise smooth signals can be represented as sparse and compressible coefficients. These coefficients can then be effectively compressed via CS. Since a wavelet transform divides image information into layered blockwise wavelet coefficients over spatial and frequency domains, visual improvement can be attained by an appropriate perceptually weighted CS scheme. We introduce such a method in this paper and compare it to conventional CS. The resulting visual CS model is shown to deliver improved visual reconstructions. |
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Authors:
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H Lee; H Oh; S Lee; A C Bovik |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-12-04 |
Journal Detail:
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Title: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Volume: - ISSN: 1941-0042 ISO Abbreviation: IEEE Trans Image Process Publication Date: 2012 Dec |
Date Detail:
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Created Date: 2012-12-10 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9886191 Medline TA: IEEE Trans Image Process Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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