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» From Learning Models of Natural Image Patches to Whole Image...
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ICCV
2011
IEEE
12 years 3 months ago
From Learning Models of Natural Image Patches to Whole Image Restoration
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
Daniel Zoran, Yair Weiss
CVPR
2007
IEEE
14 years 5 months ago
Mapping Natural Image Patches by Explicit and Implicit Manifolds
Image patches are fundamental elements for object modeling and recognition. However, there has not been a panoramic study of the structures of the whole ensemble of natural image ...
Kent Shi, Song Chun Zhu
IDA
2009
Springer
13 years 10 months ago
Estimating Markov Random Field Potentials for Natural Images
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...
Urs Köster, Jussi T. Lindgren, Aapo Hyvä...
CVPR
2009
IEEE
14 years 11 months ago
Contextual Restoration of Severely Degraded Document Images
We propose an approach to restore severely degraded document images using a probabilistic context model. Un- like traditional approaches that use previously learned prior models...
Jyotirmoy Banerjee, Anoop M. Namboodiri, C. V. Jaw...
ICIP
2003
IEEE
13 years 9 months ago
Perceptual regularization functionals for natural image restoration
Regularization constraints are necessary in inverse problems such as image restoration, optical flow computation or shape from shading to avoid the singularities in the solution....
Juan Gutierrez, Jesus Malo, Francesc J. Ferri