A. Pizurica: research interests
Markov Random Field models, inference algorithms and applications
I am interested in spatial context modeling using Markov Random Fields and
in developing efficient inference algorithms for graphical models.
These models and inference methods find many interesting applications, like in image restoration and inpainting,
theoretical studies of structured sparsity, tomographic reconstructions etc. Some concrete research topics here are:
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Hierarchical and anisotropic Markov Random Field models for modeling image edges and clustering of image wavelet (and x-let) coefficients
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Inference by stochastic sampling
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Inference by message passing algorithms
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Applications in image and video restoration
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Applications in image and video inpainting
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Structured sparsity models and applications in tomographic reconstructions
Selected related publications
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A. Pizurica, W. Philips, I. Lemahieu, and M. Acheroy,
"A Wavelet-Based Image Denoising Technique Using Spatial Priors",
in Proc. of the IEEE International Conf. on Image Proc. (ICIP 2000), pp. 296—299,
Vancouver, BC, Canada, Sep, 2000.
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A. Pizurica, W. Philips, I. Lemahieu, and M. Acheroy,
"The Application of Markov Random Field Models
to Wavelet-Based Image Denoising",
in Imaging and Vision Systems: Theory, Assessment and Applications,
editors J. Blanc-Talon and D. Popescu, NOVA Science Books, Huntington, USA, 2001.
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A. Pižurica, J. Aeltermana, F. Bai, S. Vanloocke, H.Q. Luong, B. Goossens and W. Philips,
"On structured sparsity and selected applications in
tomographic imaging"
SPIE Conference Wavelets and Sparsity XIV, 2011, Aug 21-24, San Diego, USA, 12 pages (Invited paper).
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T. Ružic, H. Luong, A. Pižurica, and W. Philips,
“Single image example-based super-resolution using cross-scale patch matching and Markov random field modelling”,
Internat Conf on Image Analysis and Recognition (ICIAR), 2011, June 22-24, Burnaby, Canada, Vol. 6753, pp. 11-20.
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F. Bai, A. Pižurica, S. Van Loocke, A. Franchois, D. De Zutter, W. Philips,
"Quantitative Microwave Tomography from Sparse Measurements using a Robust Huber Regularizer"
in IEEE International Conference on Image Processing (ICIP 2012), Orlando, Florida, USA, pp. 2073-2076, 2012.
Educational demo programs
Samples from the Ising model
Get a program for generating these samples
Samples from an anisotropic MRF model
Get a program for generating these samples