Computer Vision, Graphics, and Image Processing
Visual reconstruction
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale minimization of global energy functions in some visual recovery problems
CVGIP: Image Understanding
Fourier-related transforms, fast algorithms and applications
Fourier-related transforms, fast algorithms and applications
Robot Vision
Signal Processing for Computer Vision
Signal Processing for Computer Vision
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
An Accurate and Efficient Bayesian Method for Automatic Segmentation of Brain MRI
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Image Segmentation by Flexible Models Based on Robust Regularized Networks
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Hidden Markov Measure Field Models for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The MPM-MAP algorithm for motion segmentation
Computer Vision and Image Understanding
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Edge-Preserving Image Denoising and Estimation of Discontinuous Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image classification based on Markov random field models with Jeffreys divergence
Journal of Multivariate Analysis - Special issue dedicated to Professor Yasunori Fujikoshi
A General Bayesian Markov Random Field Model for Probabilistic Image Segmentation
IWCIA '09 Proceedings of the 13th International Workshop on Combinatorial Image Analysis
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Edge structure preserving image denoising
Signal Processing
Beta-measure for probabilistic segmentation
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Alpha Markov Measure Field model for probabilistic image segmentation
Theoretical Computer Science
3D Line Drawing for Archaeological Illustration
International Journal of Computer Vision
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Entropy controlled gauss-markov random measure field models for early vision
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Crease detection on noisy meshes via probabilistic scale selection
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
A method of motion segmentation based on region shrinking
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Dense optic flow with a bayesian occlusion model
SCVMA'04 Proceedings of the First international conference on Spatial Coherence for Visual Motion Analysis
Bayesian multiscale analysis of images modeled as Gaussian Markov random fields
Computational Statistics & Data Analysis
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We present a class of models, derived from classical discrete Markov random fields, that may be used for the solution of ill-posed problems in image processing and in computational vision. They lead to reconstrucion algorithms that are flexible, computationally efficient, and biologically plausible. To illustrate their use, we present their application to the reconstruction of the dominant orientation and direction fields, to the classification of multiband images, and to image quantization and filtering.