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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/9403
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dc.contributor.authorGupta, Karunesh Kumar-
dc.contributor.authorGupta, Rajiv-
dc.date.accessioned2023-03-01T07:02:19Z-
dc.date.available2023-03-01T07:02:19Z-
dc.date.issued2008-
dc.identifier.urihttps://ieeexplore.ieee.org/document/4426061-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9403-
dc.description.abstractIn this paper, a new wavelet shrinkage denoising algorithm is presented. The algorithm uses wavelet transform (WT) to extract information about sharp variation in multiresolution images and applies shrinkage function adapting the image features. The features are detected by energy of neighboring pixels, whereas in standard wavelet methods, the empirical wavelet coefficients shrink pixel by pixel, on the basis of their individual magnitude. The shrinkage function is optimized by differential Evolution (DE)en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectWavelet coefficientsen_US
dc.subjectNoise reductionen_US
dc.subjectWavelet transformsen_US
dc.subjectImage reconstructionen_US
dc.titleAdaptive Shrinkage Function Optimization by Differential Evolutionen_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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