Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Elements of information theory
Elements of information theory
Visual reconstruction with discontinuities using variational methods
Image and Vision Computing
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Variational methods in image segmentation
Variational methods in image segmentation
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
The digital TV filter and nonlinear denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Unconstrained Multiphase Thresholding Approach for Image Segmentation
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Region based image segmentation using a modified Mumford-Shah algorithm
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Γ-convergence approximation to piecewise smooth medical image segmentation
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
A probabilistic multi-phase model for variational image segmentation
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
| Hi-index | 0.00 |
Piecewise constant Mumford-Shah segmentation[17] has been rediscovered by Chan and Vese [6] in the context of region based active contours. The work of Chan and Vese demonstrated many practical applications thanks to their clever numerical implementation using the level-set technology of Osher and Sethian [18]. The current work proposes a Γ-convergence formulation to the piecewise constant Mumford-Shah model, and demonstrates its simple implementation by the iterated integration of a linear Poisson equation. The new formulation makes unnecessary some intermediate tasks like normal data extension and level-set reinitialization, and thus lowers the computational complexity.