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2010
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13 years 4 months ago
Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content
Across the field of inverse problems in image and video processing, nearly all algorithms have various parameters which need to be set in order to yield good results. In practice, ...
Xiang Zhu, Peyman Milanfar
CVPR
2009
IEEE
15 years 4 months ago
StaRSaC: Stable Random Sample Consensus for Parameter Estimation
We address the problem of parameter estimation in presence of both uncertainty and outlier noise. This is a common occurrence in computer vision: feature localization is perform...
Jongmoo Choi, Gérard G. Medioni
CVPR
2009
IEEE
15 years 4 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
CVPR
2006
IEEE
14 years 11 months ago
An Intensity-augmented Ordinal Measure for Visual Correspondence
Determining the correspondence of image patches is one of the most important problems in Computer Vision. When the intensity space is variant due to several factors such as the ca...
Anurag Mittal, Visvanathan Ramesh
ICIP
2005
IEEE
14 years 11 months ago
Image denoising in nonlinear scale-spaces: automatic scale selection via cross-validation
Multiscale, i.e. scale-space image analysis is a powerful framework for many image processing tasks. A fundamental issue with such scale-space techniques is the automatic selectio...
George Papandreou, Petros Maragos