Name
Abstract | ||
|---|---|---|
We propose a novel multiphase segmentation model built upon the celebrated phase transition model of Modica and Mortola in material sciences and a properly synchronized fitting term that complements it. The proposed sine-sinc model outputs a single multiphase distribution from which each individual segment or phase can be easily extracted. Theoretical analysis is developed for the Gamma-convergence behavior of the proposed model and the existence of its minimizers. Since the model is not quadratic nor convex, for computation we adopted the convex-concave procedure ( CCCP) that has been developed in the literatures of both computational nonlinear PDEs and neural computation. Numerical details and experiments on both synthetic and natural images are presented. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1137/060662708 | SIAM JOURNAL ON APPLIED MATHEMATICS |
Keywords | Field | DocType |
multiphase,segmentation,variational,partial differential equation,Modica-Mortola model,phase transition,Gamma-convergence,convex splitting,convex-concave procedure | Mathematical optimization,Nonlinear system,Segmentation,Models of neural computation,Quadratic equation,Regular polygon,Image segmentation,Partial differential equation,Mathematics,Computation | Journal |
Volume | Issue | ISSN |
67 | 5 | 0036-1399 |
Citations | PageRank | References |
38 | 1.40 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoon Mo Jung | 1 | 58 | 6.09 |
| Sung Ha Kang | 2 | 430 | 29.39 |
| Jianhong Shen | 3 | 376 | 34.18 |