Variational Models for Image Restoration with Applications in Deformable Registration

Add to your list(s) Download to your calendar using vCal

• Ke Chen (University of Liverpool)
• Thursday 29 November 2012, 15:00-16:00
• MR 14, CMS.

If you have a question about this talk, please contact Carola-Bibiane Schoenlieb.

Variational models offer high resolution solutions of many common image processing tasks by treating images as functions rather than matrices. In this talk, I first discuss the simple models based on mean curvature by Lysaker-Osher-Tai (2004) and Zhu-Chan (2008,2012) as well as total variation (TV) regularisation by Rudin-Osher-Fatemi (1992). Recent results on choosing the best coupling parameter in a TV model and on fast algorithms for curvature models are also shown.

Then I discuss the modeling problem of image registration which is another important task in image processing, where regularization is a major issue in designing new models. The prevously well-known regularisers such as the TV and optical flow based ones turn out to be much less effective than a mean curvature regulariser. Finally I show how to use the mean curvature to design a registration model suitable for multi-modality registration.

This talk is part of the Applied and Computational Analysis series.

This talk is included in these lists:

• All CMS events
• All Talks (aka the CURE list)
• Applied and Computational Analysis
• CMS Events
• DAMTP info aggregator
• Featured lists
• Interested Talks
• MR 14, CMS
• My seminars
• Type the title of a new list here
• bld31

Note that ex-directory lists are not shown.