Hierarchical Multiscale Modeling of Wavelet-Based Correlations
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Measuring and Improving Image Resolution by Adaptation of the Reciprocal Cell
Journal of Mathematical Imaging and Vision
Integration of form and motion within a generative model of visual cortex
Neural Networks - 2004 Special issue Vision and brain
Real-time detection of steam in video images
Pattern Recognition
Extrapolative Spatial Models for Detecting Perceptual Boundaries in Colour Images
International Journal of Computer Vision
A statistical framework based on a family of full range autoregressive models for edge extraction
Pattern Recognition Letters
Two-phase Web site classification based on Hidden Markov Tree models
Web Intelligence and Agent Systems
Iterative desensitisation of image restoration filters under wrong PSF and noise estimates
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Technical Section: Circular spatial filtering under high-noise-variance conditions
Computers and Graphics
Sparse Multiscale Patches (SMP) for Image Categorization
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Sparse Multiscale Patches for Image Processing
Emerging Trends in Visual Computing
Multiscale fusion of wavelet-domain hidden Markov tree through graph cut
Image and Vision Computing
Intelligent Processing of Medical Images in the Wavelet Domain
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Modelling Stem Cells Lineages with Markov Trees
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
IEEE Transactions on Image Processing
Removal of correlated noise by modeling the signal of interest in the wavelet domain
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Stochastic texture analysis for monitoring stochastic processes in industry
Pattern Recognition Letters
Color texture analysis using the wavelet-based hidden Markov model
Pattern Recognition Letters
Image processing using 3-state cellular automata
Computer Vision and Image Understanding
Model-based compressive sensing
IEEE Transactions on Information Theory
Variable density compressed image sampling
IEEE Transactions on Image Processing
LMMSE-based image denoising in nonsubsampled contourlet transform domain
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Journal of Mathematical Imaging and Vision
Document image analysis: issues, comparison of methods and remaining problems
Artificial Intelligence Review
A robust and fast non-local means algorithm for image denoising
Journal of Computer Science and Technology
Global optimization of wavelet-domain hidden Markov tree for image segmentation
Pattern Recognition
Computers and Electrical Engineering
A new fuzzy-based wavelet shrinkage image denoising technique
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Automatic texture segmentation based on wavelet-domain hidden markov tree
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Flame image of pint-sized power plant's boiler denoising using wavelet-domain HMT models
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
A wavelet-based fragile watermarking scheme for secure image authentication
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Journal of Mathematical Imaging and Vision
Adaptive Compressed Image Sensing Using Dictionaries
SIAM Journal on Imaging Sciences
Λ-neighborhood wavelet shrinkage
Computational Statistics & Data Analysis
A new fuzzy additive noise reduction method
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Edge structure preserving image denoising using OAGSM/NC statistical model
Digital Signal Processing
A clustering approach for estimating parameters of a profile hidden Markov model
International Journal of Data Mining and Bioinformatics
Image denoising using SVM classification in nonsubsampled contourlet transform domain
Information Sciences: an International Journal
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
Multiscale discriminant saliency for visual attention
ICCSA'13 Proceedings of the 13th international conference on Computational Science and Its Applications - Volume 1
Simplified noise model parameter estimation for signal-dependent noise
Signal Processing
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Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint probability density of the wavelet coefficients of real-world data. One potential drawback to the HMT framework is the need for computationally expensive iterative training to fit an HMT model to a given data set (e.g., using the expectation-maximization algorithm). We greatly simplify the HMT model by exploiting the inherent self-similarity of real-world images. The simplified model specifies the HMT parameters with just nine meta-parameters (independent of the size of the image and the number of wavelet scales). We also introduce a Bayesian universal HMT (uHMT) that fixes these nine parameters. The uHMT requires no training of any kind, while extremely simple, we show using a series of image estimation/denoising experiments that these new models retain nearly all of the key image structure modeled by the full HMT. Finally, we propose a fast shift-invariant HMT estimation algorithm that outperforms other wavelet-based estimators in the current literature, both visually and in mean square error