In 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
Related publications
Journal articles
Cho, D., A. Wong, D. 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 Imagery
", 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. Xu, A. Wong, and D. A. Clausi, "Feature Extraction for Hyperspectral Imagery via Ensemble Localized Manifold Learning", IEEE Geoscience and Remote Sensing Letters, vol. 12, issue 12, 2015. Details
Li, F., L. Xu, A. Wong, and D. A. Clausi, "QMCTLS: Quasi Monte Carlo Texture Likelihood Sampling for Despeckling of Complex Polarimetric SAR Images", IEEE Geoscience and Remote Sensing Letters, vol. 12, issue 7, February, 2015. Details
Xu, L., A. Wong, F. Li, and D. A. Clausi, "Extraction of Endmembers From Hyperspectral Images Using A Weighted Fuzzy Purified-Means Clustering Model", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, issue 2, 2015. Details
Xu, L., F. Li, A. Wong, and D. A. Clausi, "Hyperspectral Image Denoising Using a Spatial–Spectral Monte Carlo Sampling Approach", 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. Haider, A. Wong, D. Lui, A. 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. Xu, D. 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. Mishra, P. Fieguth, and D. A. Clausi, "Sparse reconstruction of breast MRI using homotopic L0 minimization in a regional sparsified domain", IEEE Transactions on Biomedical Engineering, vol. 60, no. 3, pp. 743 - 52, 2013. Details
Campaigne, W., and P. Fieguth, "Frozen State Hierarchical Annealing", 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 system", International Journal of Document Analysis and Recognition, vol. 15, no. 3: Springer, pp. 253 - 266, 2012. Details
Zhang, W., A. Wong, A. Mishra, P. Fieguth, and D. A. Clausi, "Efficient globally optimal registration of remote sensing imagery via quasi-random scale-space structural correlation energy functional", 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 model",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 map", Journal of Mathematical Imaging and Vision, pp. 1-15, 2011. Details
Wong, A., A. Mishra, W. Zhang, P. Fieguth, and D. A. Clausi, "Stochastic image denoising based on Markov-chain Monte Carlo sampling", Signal Processing, vol. 91, issue 8, pp. 2112 - 2120, 2011. Details
Mishra, A., A. Wong, D. A. Clausi, and P. Fieguth, "Quasi-random nonlinear scale space", 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 processes", Automatica, vol. 37, pp. 325–340, 2001. Details
Fieguth, P., "Multiply-rooted multiscale models for large-scale estimation", 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 images", 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 systems", 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 estimation", 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 data", 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. Shafiee, A. Wong, F. Li, L. Wang, and D. A. Clausi, "Oil Spill Candidate Detection from SAR Imagery Using a Thresholding-Guided Stochastic Fully-Connected Conditional Random Field Model", CVPR 2015 Earthvision Workshop, Accepted. Details
Shafiee, M. J., A. Chung, A. Wong, and P. Fieguth, "IMPROVED FINE STRUCTURE MODELING VIA GUIDED STOCHASTIC CLIQUE FORMATION IN FULLY CONNECTED CONDITIONAL RANDOM FIELDS", 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 Symmetry", IEEE International Conference on Image Processing, Accepted. Details
Li, F., M. J. Shafiee, A. Chung, B. Chwyl, F. Kazemzadeh, A. Wong, and J. S. Zelek, "HIGH DYNAMIC RANGE MAP ESTIMATION VIA FULLY CONNECTED RANDOM FIELDS WITH STOCHASTIC CLIQUES", International Conference on Image Processing, April, Accepted. Details
Scharfenberger, C., A. Jain, A. Wong, and P. Fieguth, "Image saliency detection via multi-scale statistical non-redundancy modeling", IEEE Conference on Image Processing, 2014. Details
Shafiee, M. J., A. Wong, P. Siva, and P. Fieguth, "EFFICIENT BAYESIAN INFERENCE USING FULLY CONNECTED CONDITIONAL RANDOM FIELDS WITH STOCHASTIC CLIQUES", 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. Wong, P. Fieguth, and D. A. Clausi, "Multi-Scale 3D representation via volumetric quasi-random scale space", 18th IEEE International Conference on Image Processing (ICIP 2011), September, 2011. Details
Mishra, A., A. Wong, D. A. Clausi, and P. Fieguth, "A Bayesian information flow approach to image segmentation",7th Canadian Conference on Computer and Robot Vision, Ottawa, Ontario, Canada, March, 2010. Details
Wong, A., A. Mishra, D. A. Clausi, and P. Fieguth, "Mammogram image superresolution based on statistical moment analysis", 7th Canadian Conference on Computer and Robot Vision, Ottawa, Ontario, Canada, IEEE Computer Society, pp. 339–346, March, 2010. Details
Ahmadi, E., Z. Azimifar, P. Fieguth, and S. Ayatollahi, "Image synthesis using conditional random fields", 17th IEEE International Conference on Image Processing (ICIP), pp. 3997 - 4000, 2010. Details
Liu, Y., A. Wong, and P. Fieguth, "Remote sensing image synthesis", 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2467 -2470, 2010. Details
Mohebi, A., Y. Liu, and P. Fieguth, "Hierarchical sampling with constraints", 6th International Conference on Image Analysis and Recognition, pp. 23 - 32, 2009. Details
Liu, Y., and P. Fieguth, "Image resolution enhancement with hierarchical hidden fields", 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 reconstruction", 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. Mishra, P. Fieguth, and D. A. Clausi, "An adaptive Monte Carlo approach to nonlinear image denoising",19th International Conference on Pattern Recognition, Tampa, Florida, USA, Dec. 8 - 11, 2008. Details
Mishra, A., A. Wong, D. A. Clausi, and P. Fieguth, "Adaptive nonlinear image denoising and restoration using a cooperative Bayesian estimation approach", 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 images", 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 models", 12th IEEE International Conference on Image Processing: Springer, 2005. Details
Kachouie, N. Nezamoddin, L. J. Lee, and P. Fieguth, "A probabilistic living cell segmentation model", 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 resolutions", 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 model", 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 statistics", 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 models", 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 statistics", 2003 IEEE Workshop on Statistical Signal Processing, 2003. Details
Alexander, S. K., P. Fieguth, and E. Vrscay, "Hierarchical annealing for random image synthesis", 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 fields", ICIP '03, vol. 1, Spain, 2003. Details
Wesolkowski, S., and P. Fieguth, "A probabilistic framework for image segmentation", 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 segmentation", 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 sequences", 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 statistics", International Conference on Image Processing, Rochester, NY, 2002. Details
Wesolkowski, S., and P. Fieguth, "Adaptive color image segmentation using Markov random fields", International Conference on Pattern Recognition, Rochester, NY, 2002. Details
Wesolkowski, S., and P. Fieguth, "Gibbs random field based vector quantization", NATO ASI Learning Theory and Practice Workshop, Belgium, 2002. Details
Azimifar, Z., P. Fieguth, and E. Jernigan, "Hierarchical multiscale modeling of wavelet-based correlations",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 coefficients", International Conference on Image Processing, vol. 3, Greece, 2001. Details
Carballo, G. F., and P. Fieguth, "Probabilistic cost functions for network flow phase unwrapping", IEEE International Geoscience and Remote Sensing Symposium, vol. 3, pp. 1531 - 1533, 1999. Details
Fieguth, P., "Foveated multiscale models for large-scale estimation", 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 analysis", 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 Processing
", 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 Problems",Department of Electrical Engineering and Computer Science, Cambridge, Massachusetts, Massachusetts Institute of Technology, 1995. Details
