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Newton-Type Algorithms for Total Variation Based Image Restoration

Author: WuZuoYu
Tutor: YangYuFei
School: Hunan University
Course: Operational Research and Cybernetics
Keywords: Image Restoration Total Variation Bounded variation Augmented Lagrangian method Ill-posed problems Semi - smooth Newton method Primitive dual set of effective operators
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 257
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Abstract


There are many factors in the process of image acquisition will lead to a decline in the quality of the image (ie, degraded ) , such as the aberration of the optical system , atmospheric turbulence , mobile , defocusing and system noise, etc. The purpose of image restoration is of the original image structure , as much as possible to restore the image of the main features of image restoration image processing is very important and challenging topic , since there are a lot of issues not fully resolved . This paper studies based on the total variation image restoration problem Newton type algorithm . text is divided into five chapters : the first chapter summarizes the basic digital image processing concept and historical origins of digital image formation and representation , an overview of the background and significance of image restoration study the second chapter describes some basic mathematical concepts and prior knowledge , including bounded variation (Bounded Vari-ation), non - smooth convex optimization , Augmented Lagrangian method , ill-posed problems and their regularization , etc. the third chapter describes the image restoration basic concepts , general image degradation model , the total variation for image restoration model and its discretization Chapter semismooth Newton method for image restoration problems , and the convergence analysis . Numerical experiments show that the method is effective . Chapter smaller computational primitive image restoration problem dual Active Set Algorithm , the algorithm is equivalent to a semi- smooth Newton method for solving a nonsmooth equations , therefore , the algorithm has a fast convergence rate . numerical experiments show that the method is indeed more than the previous chapter proposed method is much faster. Finally, a summary of the full text and pointed out that the topic needs further study .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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