251 search results - page 1 / 51 » From Learning Models of Natural Image Patches to Whole Image... |
ICCV
2011
IEEE
12 years 11 months ago
2011
IEEE
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...
CVPR
2007
IEEE
15 years 26 days ago
2007
IEEE
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 ...
IDA
2009
Springer
14 years 5 months ago
2009
Springer
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...
CVPR
2009
IEEE
15 years 6 months ago
2009
IEEE
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...
ICIP
2003
IEEE
14 years 4 months ago
2003
IEEE
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....