Stochastic Models

Stochastic ModelsIn many image processing, computer vision, and pattern recognition applications, there is often a large degree of uncertainty associated with factors such as the appearance of the underlying scene within the acquired data, the location and trajectory of the object of interest, the physical appearance (e.g., size, shape, color, etc.) of the objects being detected, etc. Given these uncertainties, there can be a wide range of possible outcomes for each of these factors that cannot be accounted for using deterministic approaches in an efficient or effective manner. Stochastic models, on the other hand, allow such uncertainties to be taken into account to provide a more complete picture and a robust representation of the problem at hand. Researchers in the VIP lab are investigating novel approaches for constructing robust, large-scale stochastic models to better tackle image processing and computer vision problems such as image denoising, segmentation, registration, and classification in an robust and efficient manner.

Related people

Directors

Alexander Wong, David A. Clausi, Paul Fieguth

Students

Ameneh Boroomand, Andre Carrington, Shahid Haider, M. Javad Shafiee, Keyvan Kasiri, Linlin Xu, Shelley Wang, Bi Hongbo, Audrey Chung, Hicham Sekkati

Alumni

Amir H. Shabani, Wen Zhang, Ying Liu, Simon Alexander, Chenyi Liu, Aanchal Jain, Andrew Cameron, Dorothy Lui, Shimon Schwartz, Zohreh Azimifar

Related demos

Porous Media
VIP-LowLight

Related publications

Journal articles

Cho, D.A. WongD. A. Clausi, J. Callaghan, and J. Yates, "Markov-Chain Monte Carlo based Image Reconstruction for Streak Artifact Reduction on Contrast Enhanced Computed Tomography", Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Accepted. Details

Wong, A., and J. Scharcanski, "Monte Carlo Despeckling of Transrectal Ultrasound (TRUS) Images of the Prostate",Digital Signal Processing, Accepted. Details

Xu, L., J. M. Shafiee, A. Wong, and D. A. Clausi, "Fully-Connected Continuous Conditional Random Field With Stochastic Cliques for Dark-spot Detection In SAR Imagerypdf", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, February, Accepted. Details

Schwartz, S.A. Wong, and D. A. Clausi, "Optimized sampling distribution based on nonparametric learning for improved compressive sensing performance", Journal of Visual Communication and Image Representation, vol. 31, pp. 26-40, May, 2015. Details

Li, F.L. XuA. Wong, and D. A. Clausi, "Feature Extraction for Hyperspectral Imagery via Ensemble Localized Manifold Learningpdf", IEEE Geoscience and Remote Sensing Letters, vol. 12, issue 12, 2015. Details

Li, F.L. XuA. Wong, and D. A. Clausi, "QMCTLS: Quasi Monte Carlo Texture Likelihood Sampling for Despeckling of Complex Polarimetric SAR Imagespdf", IEEE Geoscience and Remote Sensing Letters, vol. 12, issue 7, February, 2015. Details

Xu, L.A. WongF. Li, and D. A. Clausi, "Extraction of Endmembers From Hyperspectral Images Using A Weighted Fuzzy Purified-Means Clustering Modelpdf", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, issue 2, 2015. Details

Xu, L.F. LiA. Wong, and D. A. Clausi, "Hyperspectral Image Denoising Using a Spatial–Spectral Monte Carlo Sampling Approachpdf", IEEE Journal of Selected Topics on Applied Earth Observations and Remote Sensing, vol. 8, issue 6: IEEE, 2015. Detailsnsic Representation of Hyperspectral Imagery for Unsupervised Feature Extraction", IEEE Transactions on Geosciences and Remote Sensing, vol. 54, issue 2: IEEE, 2015. Details

Shafiee, M. J.S. HaiderA. WongD. LuiA. Cameron, A. Modhafar, P. Fieguth, and M. A. Haider, "Apparent Ultra-High b-value Diffusion-Weighted Image Reconstruction via Hidden Conditional Random Fields", TRANSACTIONS ON MEDICAL IMAGING, vol. 34, no. 5: IEEE, 2015. Details

Wang, C., L. XuD. A. Clausi, and A. Wong, "A Bayesian Joint Decorrelation and Despeckling approach for speckle reduction of SAR Images", Vision Letters, vol. 1, issue 1, 2015. Details

Wong, A.A. MishraP. Fieguth, and D. A. Clausi, "Sparse reconstruction of breast MRI using homotopic L0 minimization in a regional sparsified domainpdf", IEEE Transactions on Biomedical Engineering, vol. 60, no. 3, pp. 743 - 52, 2013. Details

Campaigne, W., and P. Fieguth, "Frozen State Hierarchical Annealingpdf", IEEE Transactions on Image Processing, vol. 22, no. 4, pp. 1486-1497, 2013. Details

Yousefi, M., M. Famouri, B. Nasihatkon, Z. Azimifar, and P. Fieguth, "A robust probabilistic Braille recognition systempdf", International Journal of Document Analysis and Recognition, vol. 15, no. 3: Springer, pp. 253 - 266, 2012. Details

Zhang, W.A. WongA. MishraP. Fieguth, and D. A. Clausi, "Efficient globally optimal registration of remote sensing imagery via quasi-random scale-space structural correlation energy functionalpdf", IEEE Geoscience and Remote Sensing Letters, vol. 8, issue 5, pp. 997-1001, 2011. Details

Liu, Y.A. Wong, and P. Fieguth, "Synthesis of remote sensing label fields using a tree-structured hierarchical modelpdf",IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 6, pp. 2060-2070, 2011. Details

Azimifar, Z., M. Amiri, P. Fieguth, and E. Jernigan, "Empirical study of wavelet domain image joint statistics and proposition of an efficient correlation mappdf", Journal of Mathematical Imaging and Vision, pp. 1-15, 2011. Details

Wong, A.A. MishraW. ZhangP. Fieguth, and D. A. Clausi, "Stochastic image denoising based on Markov-chain Monte Carlo samplingpdf", Signal Processing, vol. 91, issue 8, pp. 2112 - 2120, 2011. Details

Mishra, A.A. WongD. A. Clausi, and P. Fieguth, "Quasi-random nonlinear scale spacepdf", Pattern Recognition Letters, vol. 31, issue 13, pp. 1850 - 1859, 2010. Details

Ho, T. T., P. Fieguth, and A. S. Willsky, "Computationally efficient steady-state multiscale estimation for 1-D diffusion processespdf", Automatica, vol. 37, pp. 325–340, 2001. Details

Fieguth, P., "Multiply-rooted multiscale models for large-scale estimationpdf", IEEE Transactions on Image Processing, vol. 10, pp. 1676 - 1686, 2001. Details

Carballo, G. F., and P. Fieguth, "Probabilistic Cost Functions for Network Flow Phase Unwrapping", IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 5, pp. 2192 - 2201, 2000. Details

Schneider, M., P. Fieguth, W. C. Karl, and A. S. Willsky, "Multiscale statistical methods for the segmentation of signals and imagespdf", IEEE Transactions on Image Processing, vol. 9, no. 3, pp. 456 - 468, 2000. Details

Yasmin, A., P. Fieguth, and L. Deng, "Evaluation of quality of speech enhanced by HMM and AR model-based systemspdf", The Journal of the Acoustical Society of America, vol. 106, no. 4: ASA, pp. 2181-2181, 1999. Details

Irving, W. W., P. Fieguth, and A. S. Willsky, "An overlapping tree approach to multiscale stochastic modeling and estimationpdf", IEEE Transactions on Image Processing, vol. 6, no. 11, pp. 1517 - 1529, 1997. Details

Wunsch, C., D. Menemenlis, P. Fieguth, and A. S. Willsky, "Adaptation of a fast optimal interpolation algorithm to the mapping of oceanographic datapdf", Journal of Geophysical Research, vol. 102, issue C5: AGU, pp. 10573 - 10584, 1997. Details

Fieguth, P., and A. S. Willsky, "Fractal estimation using models on multiscale trees", IEEE Transactions on Signal Processing, vol. 44, no. 5, pp. 1297 - 1300, 1996. Details

Conference papers

Xu, L.M. J. ShafieeA. WongF. LiL. Wang, and D. A. Clausi, "Oil Spill Candidate Detection from SAR Imagery Using a Thresholding-Guided Stochastic Fully-Connected Conditional Random Field Modelpdf", CVPR 2015 Earthvision Workshop, Accepted. Details

Shafiee, M. J.A. ChungA. Wong, and P. Fieguth, "IMPROVED FINE STRUCTURE MODELING VIA GUIDED STOCHASTIC CLIQUE FORMATION IN FULLY CONNECTED CONDITIONAL RANDOM FIELDSpdf", IEEE Conference on Image Processing, Accepted. Details

Liu, L.P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Details

Mwangi, G., C. Garbe, and P. Fieguth, "Probabilistic Continuous Edge Detection using Local Symmetrypdf", IEEE International Conference on Image Processing, Accepted. Details

Li, F.M. J. ShafieeA. ChungB. ChwylF. KazemzadehA. Wong, and J. S. Zelek, "HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM FIELDS WITH STOCHASTIC CLIQUESpdf", International Conference on Image Processing, April, Accepted. Details

Scharfenberger, C.A. JainA. Wong, and P. Fieguth, "Image saliency detection via multi-scale statistical non-redundancy modelingpdf", IEEE Conference on Image Processing, 2014. Details

Shafiee, M. J.A. WongP. Siva, and P. Fieguth, "EFFICIENT BAYESIAN INFERENCE USING FULLY CONNECTED CONDITIONAL RANDOM FIELDS WITH STOCHASTIC CLIQUESpdf", International Conference on Image Processing, IEEE , 2014. Details

Sachett~Medeiros, R., J. Scharcanski, and A. Wong, "Skin Detection for Hand Gesture Segmentation using Multi-scale Stochastic Color Texture Models", IEEE International Conference on Multimedia and Expo, 2013. Details

Liu, L., B. Yang, P. Fieguth, Z. Yang, and Y. Wei, "BRINT: A Binary Rotation Invariant and Noise Tolerant Texture Descriptor", International Conference on Image Processing, Melbourne, 2013. Details

Shafiee, M. J.A. Wong, and Z. Azimifar, "A Novel Hierarchical Model-Based Frame Rate Up-Conversion via Spatio-temporal Conditional Random Fields", IEEE International Symposium of Multimedia , 2012. Details

Mishra, A.A. WongP. Fieguth, and D. A. Clausi, "Multi-Scale 3D representation via volumetric quasi-random scale spacepdf", 18th IEEE International Conference on Image Processing (ICIP 2011), September, 2011. Details

Mishra, A.A. WongD. A. Clausi, and P. Fieguth, "A Bayesian information flow approach to image segmentationpdf",7th Canadian Conference on Computer and Robot Vision, Ottawa, Ontario, Canada, March, 2010. Details

Wong, A.A. MishraD. A. Clausi, and P. Fieguth, "Mammogram image superresolution based on statistical moment analysispdf", 7th Canadian Conference on Computer and Robot Vision, Ottawa, Ontario, Canada, IEEE Computer Society, pp. 339–346, March, 2010. Details

Ahmadi, E., Z. AzimifarP. Fieguth, and S. Ayatollahi, "Image synthesis using conditional random fieldspdf", 17th IEEE International Conference on Image Processing (ICIP), pp. 3997 - 4000, 2010. Details

Liu, Y.A. Wong, and P. Fieguth, "Remote sensing image synthesispdf", 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2467 -2470, 2010. Details

Mohebi, A.Y. Liu, and P. Fieguth, "Hierarchical sampling with constraintspdf", 6th International Conference on Image Analysis and Recognition, pp. 23 - 32, 2009. Details

Liu, Y., and P. Fieguth, "Image resolution enhancement with hierarchical hidden fieldspdf", 6th International Conference on Image Analysis and Recognition, pp. 73 - 82, 2009. Details

Liu, Y., and P. Fieguth, "Parallel hidden hierarchical fields for multi-scale reconstructionpdf", 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 70–83, 2009. Details

Liu, Y.A. Mohebi, and P. Fieguth, "Modeling of multiscale porous media using multiple Markov random fields", Fourth Biot Conference on Poromechanics, New York, 2009. Details

Wong, A.A. MishraP. Fieguth, and D. A. Clausi, "An adaptive Monte Carlo approach to nonlinear image denoisingpdf",19th International Conference on Pattern Recognition, Tampa, Florida, USA, Dec. 8 - 11, 2008. Details

Mishra, A.A. WongD. A. Clausi, and P. Fieguth, "Adaptive nonlinear image denoising and restoration using a cooperative Bayesian estimation approachpdf", 6th Indian Conference on Computer Vision, Graphics Image Processing, Bhubaneswar, India, Dec. 16 - 19 , 2008. Details

Mohebi, A., and P. Fieguth, "Posterior sampling of scientific imagespdf", 2006 International Conference on Image Analysis and Recognition, Portugal, Springer, 2006. Details

Jin, F.P. Fieguth, and L. Winger, "Image denoising using complex wavelets and Markov prior modelspdf", 12th IEEE International Conference on Image Processing: Springer, 2005. Details

 

Kachouie, N. NezamoddinL. J. Lee, and P. Fieguth, "A probabilistic living cell segmentation modelpdf", International Conference on Image Analysis and Recognition, vol. 1, 2005. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Correlated wavelet shrinkage: models of local random fields across multiple resolutionspdf", International Conference on Image Analysis and Recognition, vol. 3, 2005. Details

Deng, H., and D. A. Clausi, "Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field modelpdf", IEEE Transactions on Geoscience and Remote Sensing, vol. 43, issue 12, pp. 528 - 538, 2005. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Textures and wavelet-domain joint statisticspdf", 2004 International Conference on Image Analysis and Recognition, Portugal, 2004. Details

Lee, L. J., H. Attias, L. Deng, and P. Fieguth, "A multimodal variational approach to learning and inference in switching state space modelspdf", 37th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Montreal, 2004. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Hierarchical Markov models for wavelet-domain statisticspdf", 2003 IEEE Workshop on Statistical Signal Processing, 2003. Details

Alexander, S. K.P. Fieguth, and E. Vrscay, "Hierarchical annealing for random image synthesispdf", Fourth International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2003), Portugal, 2003. Details

Fieguth, P., "Hierarchical posterior sampling for images and random fieldspdf", ICIP '03, vol. 1, Spain, 2003. Details

Wesolkowski, S., and P. Fieguth, "A probabilistic framework for image segmentationpdf", IEEE International Conference on Image Processing, Spain, 2003. Details

Wesolkowski, S., and P. Fieguth, "A Markov random fields model for hybrid edge and region based colour image segmentationpdf", 15th Canadian Conference on Electrical and Computer Engineering , vol. 2, pp. 945 - 949, 2002. Details

Khellah, F. M., and P. Fieguth, "Efficient interpolation of large image sequencespdf", IEEE International Geoscience And Remote Sensing Symposium, vol. 6, Toronto, pp. 3332 - 3334, 2002. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Towards random field modeling of wavelet statisticspdf", International Conference on Image Processing, Rochester, NY, 2002. Details

Wesolkowski, S., and P. Fieguth, "Adaptive color image segmentation using Markov random fieldspdf", International Conference on Pattern Recognition, Rochester, NY, 2002. Details

Wesolkowski, S., and P. Fieguth, "Gibbs random field based vector quantizationpdf", NATO ASI Learning Theory and Practice Workshop, Belgium, 2002. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Hierarchical multiscale modeling of wavelet-based correlationspdf",Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, pp. 850–860, 2002. Details

Azimifar, Z.P. Fieguth, and E. Jernigan, "Wavelet shrinkage with correlated wavelet coefficientspdf", International Conference on Image Processing, vol. 3, Greece, 2001. Details

Carballo, G. F., and P. Fieguth, "Probabilistic cost functions for network flow phase unwrappingpdf", IEEE International Geoscience and Remote Sensing Symposium, vol. 3, pp. 1531 - 1533, 1999. Details

Fieguth, P., "Foveated multiscale models for large-scale estimationpdf", International Conference on Image Processing, 1999. Details

Fieguth, P., and A. S. Willsky, "Multiresolution models for fractals and their uses in statistical signal and image processing", IEEE Conference on Nonlinear Signal and Image Processing, Greece, pp. 779 - 782, 1995. Details

Fieguth, P., W. W. Irving, and A. S. Willsky, "Multiresolution model development for overlapping trees via canonical correlation analysispdf", International Conference on Image Processing, vol. 1, pp. 45 - 48, 1995. Details

Book chapters

Mohebi, A., and P. Fieguth, "Constrained Sampling Using Simulated Annealing", Image Analysis and Recognition, vol. 4633: Springer Berlin / Heidelberg, pp. 198 - 209, 2007. Details

Fieguth, P., W. Campaigne, and S. K. Alexander, "Frozen-State Hierarchical Annealing", Image Analysis and Recognition, vol. 4141: Springer Berlin / Heidelberg, pp. 41-52, 2006. Details

Fieguth, P., Handbook of Image and Video Processing (2nd Ed.), : Academic Press, pp. 361-276, 2004. Details

Fieguth, P., Handbook of Image and Video Processing, : Academic Press, 1999. Details

Books

Fieguth, P., "Statistical Image Processing and Multidimensional Modeling", Information Science and Statistics: Springer, 2010. Details

Theses

Xu, L., "Mixture of Latent Variable Models for Remotely Sensed Image Processingpdf", Department of Geography and Environmental Management, 2014. Details

Eichel, J. A.Statistical Model-Based Corneal Reconstruction, , Waterloo, ON, Canada, University of Waterloo, 2013. Details

Fieguth, P., "Application of Multiscale Estimation to Large Multidimensional Imaging and Remote Sensing Problemspdf",Department of Electrical Engineering and Computer Science, Cambridge, Massachusetts, Massachusetts Institute of Technology, 1995.  Details