Convex non-convex image segmentation
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 635-680 |
| Journal / Publication | Numerische Mathematik |
| Volume | 138 |
| Issue number | 3 |
| Online published | 6 Sep 2017 |
| Publication status | Published - Mar 2018 |
| Externally published | Yes |
Link(s)
Abstract
A convex non-convex variational model is proposed for multiphase image segmentation. We consider a specially designed non-convex regularization term which adapts spatially to the image structures for a better control of the segmentation boundary and an easy handling of the intensity inhomogeneities. The nonlinear optimization problem is efficiently solved by an alternating directions methods of multipliers procedure. We provide a convergence analysis and perform numerical experiments on several images, showing the effectiveness of this procedure.
Research Area(s)
- 47N10, 52A41, 65K10, 65K15, 90C26
Citation Format(s)
Convex non-convex image segmentation. / Chan, Raymond; Lanza, Alessandro; Morigi, Serena et al.
In: Numerische Mathematik, Vol. 138, No. 3, 03.2018, p. 635-680.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
