Gibbs Random Fields, Cooccurrences, and Texture Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational image models for GIS analysis: texture modeling as a tool for thematic mapping
Proceedings of the 6th ACM international symposium on Advances in geographic information systems
International Journal of Computer Vision
Visual models for spatial knowledge discovery
Proceedings of the 8th ACM international symposium on Advances in geographic information systems
Characteristic interaction structures in Gibbs texture modelling
Imaging and vision systems
Non-Parametric Motion Activity Analysis for Statistical Retrieval with Partial Query
Journal of Mathematical Imaging and Vision
Basic and Fine Structure of Pairwise Interactions in Gibbs Texture Models
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Strong Markov Random Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Maximum Likelihood Potential Estimates for Gibbs Random Field Image Models
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Texture Analysis by Accurate Identification of Simple Markovian Models
Cybernetics and Systems Analysis
Extending natural textures with multi-scale synthesis
Graphical Models - Special issue: Vision and computer graphics
Minimizing Nonsubmodular Functions with Graph Cuts-A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image-based quality assessment of road databases
International Journal of Geographical Information Science
International Journal of Computer Vision
Variational region-based segmentation using multiple texture statistics
IEEE Transactions on Image Processing
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Statistical priors for efficient combinatorial optimization via graph cuts
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Efficient belief propagation with learned higher-order markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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A Markov random field model with a Gibbs probability distribution (GPD) is proposed for describing particular classes of grayscale images which can be called spatially uniform stochastic textures. The model takes into account only multiple short- and long-range pairwise interactions between the gray levels in the pixels. An effective learning scheme is introduced to recover structure and strength of the interactions using maximal likelihood estimates of the potentials in the GPD as desired parameters. The scheme is based on an analytic initial approximation of the estimates and their subsequent refinement by a stochastic approximation. Experiments in modeling natural textures show the utility of the proposed model.