Mathematical approaches to digital color image denoising

dc.contributor.advisor Zhou, Haomin
dc.contributor.author Deng, Hao en_US
dc.contributor.committeeMember Dieci, Luca
dc.contributor.committeeMember Ronghua Pan
dc.contributor.committeeMember Sung Ha Kang
dc.contributor.committeeMember Wang, Yang
dc.contributor.department Mathematics en_US
dc.date.accessioned 2010-01-29T19:43:40Z
dc.date.available 2010-01-29T19:43:40Z
dc.date.issued 2009-09-14 en_US
dc.description.abstract Many mathematical models have been designed to remove noise from images. Most of them focus on grey value images with additive artificial noise. Only very few specifically target natural color photos taken by a digital camera with real noise. Noise in natural color photos have special characteristics that are substantially different from those that have been added artificially. In this thesis previous denoising models are reviewed. We analyze the strengths and weakness of existing denoising models by showing where they perform well and where they don't. We put special focus on two models: The steering kernel regression model and the non-local model. For Kernel Regression model, an adaptive bilateral filter is introduced as complementary to enhance it. Also a non-local bilateral filter is proposed as an application of the idea of non-local means filter. Then the idea of cross-channel denoising is proposed in this thesis. It is effective in denoising monochromatic images by understanding the characteristics of digital noise in natural color images. A non-traditional color space is also introduced specifically for this purpose. The cross-channel paradigm can be applied to most of the exisiting models to greatly improve their performance for denoising natural color images. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/31708
dc.publisher Georgia Institute of Technology en_US
dc.subject Cross-channel paradigm en_US
dc.subject Adaptive kernel regression en_US
dc.subject Color image denoising en_US
dc.subject Bilateral filter en_US
dc.subject.lcsh Photography Digital techniques
dc.subject.lcsh Image processing Digital techniques
dc.title Mathematical approaches to digital color image denoising en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Zhou, Haomin
local.contributor.corporatename College of Sciences
local.contributor.corporatename School of Mathematics
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relation.isOrgUnitOfPublication 85042be6-2d68-4e07-b384-e1f908fae48a
relation.isOrgUnitOfPublication 84e5d930-8c17-4e24-96cc-63f5ab63da69
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