Local weighted Gaussian curvature for image processing
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
We present a variational model with local weighted Gaussian curvature as regularizer. We show its convexity for an area-weight function and provide a closed-form solution for this case. The corresponding regularization coefficient has a theoretical bound. Moreover, we prove that the model is convex for a wide range of weight functions and show that it can be efficiently solved using splitting techniques. Finally, we demonstrate several applications of the model in image de-noising, smoothing, texture decomposition, image sharpening, and regularization-coefficient optimization.
Details
Original language | English |
---|---|
Title of host publication | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings |
Publisher | IEEE Computer Society |
Pages | 534-538 |
Number of pages | 5 |
ISBN (print) | 9781479923410 |
Publication status | Published - 2013 |
Peer-reviewed | Yes |
Publication series
Series | IEEE International Conference on Image Processing (ICIP) |
---|
Conference
Title | 2013 20th IEEE International Conference on Image Processing, ICIP 2013 |
---|---|
Duration | 15 - 18 September 2013 |
City | Melbourne, VIC |
Country | Australia |
External IDs
ORCID | /0000-0003-4414-4340/work/159608283 |
---|
Keywords
ASJC Scopus subject areas
Keywords
- convex model, Gaussian curvature, image processing, regularization, variational form