Visual reconstruction
Fast reaction, slow diffusion, and curve shortening
SIAM Journal on Applied Mathematics
Simultaneous Parameter Estimation and Segmentation of Gibbs Random Fields Using Simulated Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonconvex variational problems with anisotropic perturbations
Nonlinear Analysis: Theory, Methods & Applications
Unsupervised Texture Segmentation Using Markov Random Field Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion. II
SIAM Journal on Numerical Analysis
Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Evolutionary fronts for topology-independent shape modeling and recovery
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Variational methods in image segmentation
Variational methods in image segmentation
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A Variational Method in Image Recovery
SIAM Journal on Numerical Analysis
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
Variational approach for edge-preserving regularization using coupled PDEs
IEEE Transactions on Image Processing
Estimation of Markov random field prior parameters using Markov chain Monte Carlo maximum likelihood
IEEE Transactions on Image Processing
A Level Set Model for Image Classification
International Journal of Computer Vision
Image Segmentation by Flexible Models Based on Robust Regularized Networks
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A Variational Approach to Maximum a Posteriori Estimation for Image Denoising
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Two Variational Models for Multispectral Image Classification
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Image Sharpening by Flows Based on Triple Well Potentials
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Image Segmentation Using Some Piecewise Constant Level Set Methods with MBO Type of Projection
International Journal of Computer Vision
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A nonlinear entropic variational model for image filtering
EURASIP Journal on Applied Signal Processing
Optical aerial image partitioning using level sets based on modified Chan-Vese model
Pattern Recognition Letters
Nonparametric Bayesian Image Segmentation
International Journal of Computer Vision
Brain MR Image Segmentation Using Local and Global Intensity Fitting Active Contours/Surfaces
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Image Processing by Topological Asymptotic Expansion
Journal of Mathematical Imaging and Vision
Segmentation, Classification and Denoising of a Time Series Field by a Variational Method
Journal of Mathematical Imaging and Vision
Active contours driven by local Gaussian distribution fitting energy
Signal Processing
A brain MR image segmentation approach based on local intensity fitting curve evolution
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Medical image segmentation using active contour driven by local energy and minimal variance
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
An improved anisotropic diffusion model for detail- and edge-preserving smoothing
Pattern Recognition Letters
On the Length and Area Regularization for Multiphase Level Set Segmentation
International Journal of Computer Vision
Distance regularized level set evolution and its application to image segmentation
IEEE Transactions on Image Processing
Split Bregman method for minimization of region-scalable fitting energy for image segmentation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Application of the Topological Gradient Method to Color Image Restoration
SIAM Journal on Imaging Sciences
Discrete tomography reconstruction based on the multi-well potential
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Piecewise constant level set method for structural topology optimization with MBO type of projection
Structural and Multidisciplinary Optimization
"Influence areas" as a tool for testing of image restoration methods
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
Journal of Biomedical Imaging - Special issue on Mathematical Methods for Images and Surfaces 2011
A local modified chan–vese model for segmenting inhomogeneous multiphase images
International Journal of Imaging Systems and Technology
Surface embedding narrow volume reconstruction from unorganized points
Computer Vision and Image Understanding
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Herein, we present a variational model devoted to image classification coupled with an edge-preserving regularization process. The discrete nature of classification (i.e., to attribute a label to each pixel) has led to the development of many probabilistic image classification models, but rarely to variational ones. In the last decade, the variational approach has proven its efficiency in the field of edge-preserving restoration. In this paper, we add a classification capability which contributes to provide images composed of homogeneous regions with regularized boundaries, a region being defined as a set of pixels belonging to the same class. The soundness of our model is based on the works developed on the phase transition theory in mechanics. The proposed algorithm is fast, easy to implement, and efficient. We compare our results on both synthetic and satellite images with the ones obtained by a stochastic model using a Potts regularization.