Skip to main content


eCommons@Cornell >
Faculty of Computing and Information Science >
Center for Advance Computing >
Cornell Theory Center Technical Reports >

Please use this identifier to cite or link to this item:
Title: An Affine Scaling Algorithm for Minimizing Total Variation in Image Enhancement
Authors: Li, Yuying
Santosa, Fadil
Keywords: theory center
Issue Date: Dec-1994
Publisher: Cornell University
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.
Appears in Collections:Cornell Theory Center Technical Reports

Files in This Item:

File Description SizeFormat
94-201.pdf556.85 kBAdobe PDFView/Open
94-201.ps4.52 MBPostscriptView/Open

Refworks Export

Items in eCommons are protected by copyright, with all rights reserved, unless otherwise indicated.


© 2014 Cornell University Library Contact Us