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	Author	Rudin, Leonid I.; Osher, Stanley; Fatemi, Emad
	Title	Nonlinear total variation based noise removal algorithms			Type	Journal Article
	Year	1992	Publication	Physica D: Nonlinear Phenomena	Abbreviated Journal
	Volume	60	Issue	1-4	Pages	259-268
	Keywords	total variation filter; image denoising
	Abstract	A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lanrange multipliers. The solution is obtained using the gradient-projection method. This amounts to solving a time dependent partial differential equation on a manifold determined by the constraints. As t→∞ the solution converges to a steady state which is the denoised image. The numerical algorithm is simple and relatively fast. The results appear to be state-of-the-art for very noisy images. The method is noninvasive, yielding sharp edges in the image. The technique could be interpreted as a first step of moving each level set of the image normal to itself with velocity equal to the curvature of the level set divided by the magnitude of the gradient of the image, and a second step which projects the image back onto the constraint set.
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	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0167-2789	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	yes
	Call Number	UCF @ kdamkjer @ Rudin_1992			Serial	50
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