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  5. An Affine Scaling Algorithm for Minimizing Total Variation in Image Enhancement

An Affine Scaling Algorithm for Minimizing Total Variation in Image Enhancement

File(s)
94-201.pdf (556.85 KB)
94-201.ps (4.41 MB)
Permanent Link(s)
https://hdl.handle.net/1813/5532
Collections
Cornell Theory Center Technical Reports
Author
Li, Yuying
Santosa, Fadil
Abstract

A computational algorithm is proposed for image enhancement based on total variation minimization with constraints. This constrained minimization problem is introduced by Rudin et al [13,14,15] to enhance blurred and noisy images. Our computational algorithm solves the constrained minimization problem directly by adapting the affine scaling method for the unconstrained l 1 problem [3]. The resulting computational scheme, when viewed as an image enhancement process, has the feature that it can be used in an interactive manner in situations where knowledge of the noise level is either unavailable or unreliable. This computational algorithm can be implemented with a conjugate gradient method. It is further demonstrated that the interactive enhancement process is efficient.

Date Issued
1994-12
Publisher
Cornell University
Keywords
theory center
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/94-201
Type
technical report

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