Document Detail


Visually Weighted Compressive Sensing: Measurement and Reconstruction.
MedLine Citation:
PMID:  23221825     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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.
Authors:
H Lee; H Oh; S Lee; A C Bovik
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-12-04
Journal Detail:
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:
Created Date:  2012-12-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9886191     Medline TA:  IEEE Trans Image Process     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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