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» Bayesian Restoration of Noisy Images with the EM Algorithm
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JMIV
2007
83views more  JMIV 2007»
13 years 6 months ago
Minimization of a Detail-Preserving Regularization Functional for Impulse Noise Removal
Recently, a powerful two-phase method for restoring images corrupted with high level impulse noise has been developed. The main drawback of the method is the computational efficie...
Jian-Feng Cai, Raymond H. Chan, Carmine Di Fiore
CVPR
2008
IEEE
14 years 8 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
CVPR
2012
IEEE
11 years 8 months ago
City scale geo-spatial trajectory estimation of a moving camera
This paper presents a novel method for estimating the geospatial trajectory of a moving camera with unknown intrinsic parameters, in a city-scale urban environment. The proposed m...
Gonzalo Vaca-Castano, Amir Roshan Zamir, Mubarak S...
JMIV
2006
124views more  JMIV 2006»
13 years 6 months ago
Iterative Total Variation Regularization with Non-Quadratic Fidelity
Abstract. A generalized iterative regularization procedure based on the total variation penalization is introduced for image denoising models with non-quadratic convex fidelity ter...
Lin He, Martin Burger, Stanley Osher
ECCV
2004
Springer
13 years 11 months ago
A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection
This paper deals with the computation of optical flow and occlusion detection in the case of large displacements. We propose a Bayesian approach to the optical flow problem and s...
Christoph Strecha, Rik Fransens, Luc J. Van Gool