Abstract
Since their introduction in a classic paper by Rudin, Osher and Fatemi [695], total variation minimizing models have become one of the most popular and successful methodology for image restoration. More recently, there has been a resurgence of interest and exciting new developments, some extending the applicabilities to impainting, blind deconvolution and vector-valued images, while others offer improvements in better preservation of contrast, geometry and textures, in ameliorating the staircasing effect, and in exploiting the multiscale nature of the models. In addition, new computational methods have been proposed with improved computational speed and robustness. We shall review some of these recent developments.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Science+Business Media, Inc.
About this chapter
Cite this chapter
Chan, T., Esedoglu, S., Park, F., Yip, A. (2006). Total Variation Image Restoration: Overview and Recent Developments. In: Paragios, N., Chen, Y., Faugeras, O. (eds) Handbook of Mathematical Models in Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/0-387-28831-7_2
Download citation
DOI: https://doi.org/10.1007/0-387-28831-7_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-26371-7
Online ISBN: 978-0-387-28831-4
eBook Packages: Computer ScienceComputer Science (R0)