NDLI: Non-Local Euclidean Medians

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Non-Local Euclidean Medians

Content Provider	PubMed Central
Author	Chaudhury, Kunal N. Singer, Amit
Copyright Year	2012
Abstract	In this letter, we note that the denoising performance of Non-Local Means (NLM) can be improved at large noise levels by replacing the mean by the Euclidean median. We call this new denoising algorithm the Non-Local Euclidean Medians (NLEM). At the heart of NLEM is the observation that the median is more robust to outliers than the mean. In particular, we provide a simple geometric insight that explains why NLEM performs better than NLM in the vicinity of edges, particularly at large noise levels. NLEM can be efficiently implemented using iteratively reweighted least squares, and its computational complexity is comparable to that of NLM. We provide some preliminary results to study the proposed algorithm and to compare it with NLM.
Related Links	http://dx.doi.org/10.1109/lsp.2012.2217329
Ending Page	748
Page Count	4
Starting Page	745
File Format	PDF
ISSN	10709908
e-ISSN	15582361
Journal	IEEE signal processing letters
Issue Number	11
Volume Number	19
Language	English
Publisher Date	2012-11-01
Access Restriction	Open
Subject Keyword	Signal Processing Electrical and Electronic Engineering Applied Mathematics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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