Abstract
AbstractA total variation model for image restoration is introduced. The model utilizes a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. A local variance estimator is used to automatically adjust the regularization parameter. A generalized hierarchical decomposition of the restored image is integrated to the algorithm in order to speed‐up the performance of the update scheme. The corresponding subproblems are solved by a superlinearly convergent algorithm based on Fenchel‐duality and inexact semismooth Newton techniques. Numerical tests illustrate the performance of the algorithm. (© 2011 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
