A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gaussian pyramid wavelet transform for multiresolution analysis of images
Graphical Models and Image Processing
Markov random field modeling in image analysis
Markov random field modeling in image analysis
Hidden Markov Measure Field Models for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Infinitely Divisible Cascades to Model the Statistics of Natural Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fractal-based relaxation algorithm for shape from terrain image
Computer Vision and Image Understanding
ACM SIGGRAPH 2008 papers
Image Resolution Enhancement with Hierarchical Hidden Fields
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
A hierarchical texture model for unsupervised segmentation of remotely sensed images
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Frozen-State hierarchical annealing
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Posterior sampling of scientific images
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
Discrete Markov image modeling and inference on the quadtree
IEEE Transactions on Image Processing
Sonar image segmentation using an unsupervised hierarchical MRF model
IEEE Transactions on Image Processing
Multiscale image segmentation using wavelet-domain hidden Markov models
IEEE Transactions on Image Processing
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In any problem involving images having scale-dependent structures, a key issue is the modeling of these multi-scale characteristics. Because multi-scale phenomena frequently possess nonstationary, piece-wise multi-model behaviour, the classic hidden Markov method can not perform well in modeling such complex images. In this paper we provide a new modeling approach to extend previous hierarchical methods, with multiple hidden fields, to perform reconstruction in more complex, nonstationary contexts.