Reference : Bilateral Filter Evaluation Based on Exponential Kernels

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/7584

Title :	Bilateral Filter Evaluation Based on Exponential Kernels
Language :	English
Author, co-author :	Al Ismaeil, Kassem [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Aouada, Djamila [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Mirbach, Bruno [IEE S.A.]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2012
Main document title :	Pattern Recognition (ICPR), 2012 21st International Conference on
Publisher :	IEEE Xplore
Pages :	258 - 261
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-4673-2216-4
Event name :	Pattern Recognition (ICPR), 2012 21st International Conference on
Event date :	11-15 Nov. 2012
Event place (city) :	Tsukuba
Event country :	Japan
Abstract :	[en] The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with L1 distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels.
Target :	Others
Permalink :	http://hdl.handle.net/10993/7584

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