NDLI: C18 : A New Total Variation Based Image Denoising and Deblurring Technique

Content Provider	IEEE Xplore Digital Library
Author	Fahmy, M.F. Abdel Raheem, G.M. Mohammed, U.S. Fahmy, O.F.
Copyright Year	2013
Description	Author affiliation: Department of Electrical Engineering, Assiut University, Assiut, Egypt (Fahmy, M.F.; Abdel Raheem, G.M.; Mohammed, U.S.) \|\| Department of Electrical Engineering, Future University, Cairo, Egypt (Fahmy, O.F.)
Abstract	Total variation (TV) regularization is popular in image restoration and reconstruction due to its ability to preserve image edges. This paper, describes a new total variation based de-noising scheme. The proposed technique optimally finds the threshold level of the noisy image wavelet decomposition that minimizes the energy of the error between the restored and the noisy image. The minimization algorithm is regularized by including 1st as well as 2nd order derivatives effects of the noisy image, into the minimization scheme. Next, the problem of blind deconvolution of noisy images is addressed. First, the order of the blurring Point Spread Function (PSF), is accurately estimated using a de-noised version of the noisy blurred image. Then, the deconvolution algorithm is modified by including the effects of the 1 st as well as 2nd order derivatives of the blurred noisy images into the image update algorithm. Simulation results have shown significant performance improvements of the proposed schemes in both de-noising as well as deblurring noisy image.
Starting Page	280
Ending Page	287
File Size	4545541
Page Count	8
File Format	PDF
ISBN	9781467362191
e-ISBN	9781467362221
DOI	10.1109/NRSC.2013.6587925
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-16
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image Restoration Blind Image Deconvolution Image de-noising
Content Type	Text
Resource Type	Article

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