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AuthorSaid, Ahmed Ben
AuthorFoufou, Sebti
Available date2021-06-24T06:47:11Z
Publication Date2016
Publication NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ResourceScopus
ISSN3029743
URIhttp://dx.doi.org/10.1007/978-3-319-29451-3_25
URIhttp://hdl.handle.net/10576/20852
AbstractIn this paper, we present a Stein's Unbiased Risk Estimator (SURE) approach for Non-Local Mean filter to denoise multispectral images. We extend this filter to the vector case in order to take advantage from the additional spectral information brought by the multispectral imaging system. Experimental results show that the proposed optimized vector non-local mean filter (OVNLM) presented good denoising performance compared to several other approaches. Springer International Publishing Switzerland 2016.
SponsorThis publication was made possible by NPRP grant #4-1165- 2-453 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherSpringer Verlag
SubjectMultispectral image
Stein's Unbiased Risk Estimator
Vector non-local mean filter
TitleMultispectral image denoising using optimized vector NLM filter
TypeConference Paper
Pagination309-320
Volume Number9431
dc.accessType Abstract Only


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