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» Non-linear Bayesian Image Modelling
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ICCV
2007
IEEE
14 years 9 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
DAGM
2003
Springer
14 years 29 days ago
A Generative Model Based Approach to Motion Segmentation
We address the question of how to choose between different likelihood functions for motion estimation. To this end, we formulate motion estimation as a problem of Bayesian inferen...
Daniel Cremers, Alan L. Yuille
ICIP
1994
IEEE
14 years 9 months ago
Tomographic Reconstruction Based on Flexible Geometric Models
When dealing with ill-posed inverse problems in data analysis, the Bayesian approach allows one to use prior information to guide the result toward reasonable solutions. In this w...
K. M. Hanson, G. S. Cunningham, G. R. Jennings Jr....
ISBI
2008
IEEE
14 years 8 months ago
Segmentation of fetal 3D ultrasound based on statistical prior and deformable model
A statistical variational framework is proposed for the fetus and uterus segmentation in ultrasound images. The Rayleigh and exponential distributions are used to model the pixel ...
Jérémie Anquez, Elsa D. Angelini, Is...
CVPR
2011
IEEE
13 years 2 months ago
Blind Deconvolution Using A Normalized Sparsity Measure
Blind image deconvolution is an ill-posed problem that requires regularization to solve. However, many common forms of image prior used in this setting have a major drawback in th...
Dilip Krishnan, Rob Fergus