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Bilateral Filter Evaluation Based on Exponential Kernels
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-2298-6774
2012 (English)Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
2012.
Keyword [en]
Image edge detection, Kernel, Noise, Noise measurement, Noise reduction, Radiometry, Smoothing methods
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-107436OAI: oai:DiVA.org:kth-107436DiVA: diva2:575916
Conference
21st International Conference on Pattern Recognition (ICPR)
Funder
ICT - The Next Generation
Note

QC 20121212

Available from: 2012-12-11 Created: 2012-12-11 Last updated: 2013-04-11Bibliographically approved

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Ottersten, Björn

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CiteExportLink to record
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