Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/27325
Title: Improved decision based nonlinear Edge preserving algorithms for high Density noise removal in images
Researcher: Vijayakumar V R
Guide(s): Kanagasabapathy P
Keywords: Gaussian
Linear filters
Upload Date: 30-Oct-2014
University: Anna University
Completed Date: 01/12/2007
Abstract: Digital images are often corrupted by different types of noise namely newlineadditive white Gaussian noise impulse noise and mixed Gaussian and newlineimpulse noise Hence image denoising is one of the most common and newlineimportant image processing operations in image and video processing newlinesystems Many linear and nonlinear filtering algorithms have been proposed newlinein literature for image denoising Image edges and image details have high newlinefrequency content and carry very important information for visual perception newlineFilters having good edge and image detail preservation properties are highly newlinesuitable for digital image filtering Linear filters generally blur sharp edges newlinedestroy lines and other fine details present in the image This has led to a newlinesearch for nonlinear filtering alternatives In this thesis some improved newlinedecision based nonlinear edge preserving algorithms to remove high density newlinenoise in images are presented The proposed filters are simple and effective in newlinesuppressing different types of noise in the image with good edge and fine newlinedetail preserving characteristics newline newline
Pagination: xxviii, 170p.
URI: http://hdl.handle.net/10603/27325
Appears in Departments:Faculty of Information and Communication Engineering

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04_acknowledgement.pdf6.49 kBAdobe PDFView/Open
05_content.pdf4.71 kBAdobe PDFView/Open
06_chapter1.pdf114.17 kBAdobe PDFView/Open
07_chapter2.pdf4.72 MBAdobe PDFView/Open
08_chapter3.pdf4.01 MBAdobe PDFView/Open
09_chapter4.pdf6.06 MBAdobe PDFView/Open
10_chapter5.pdf3.46 MBAdobe PDFView/Open
11_chapter6.pdf6.46 MBAdobe PDFView/Open
12_chapter7.pdf7.98 MBAdobe PDFView/Open
13_chapter8.pdf6.83 MBAdobe PDFView/Open
14_chapter9.pdf30.14 kBAdobe PDFView/Open
15_reference.pdf38.82 kBAdobe PDFView/Open
16_publication.pdf10.01 kBAdobe PDFView/Open
17_vitae.pdf6.11 kBAdobe PDFView/Open


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