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ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
16 years 6 months ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
124
Voted
CVPR
2006
IEEE
15 years 8 months ago
Motion Patterns: High-Level Representation of Natural Video Sequences
This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...
Duangmanee Putthividhya, Te-Won Lee
VLSM
2005
Springer
15 years 7 months ago
Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
Mariano Rivera, Omar Ocegueda, José L. Marr...
NIPS
2003
15 years 3 months ago
Probabilistic Inference of Speech Signals from Phaseless Spectrograms
Many techniques for complex speech processing such as denoising and deconvolution, time/frequency warping, multiple speaker separation, and multiple microphone analysis operate on...
Kannan Achan, Sam T. Roweis, Brendan J. Frey
DAGM
2010
Springer
15 years 3 months ago
Exploiting Redundancy for Aerial Image Fusion Using Convex Optimization
Abstract. Image fusion in high-resolution aerial imagery poses a challenging problem due to fine details and complex textures. In particular, color image fusion by using virtual or...
Stefan Kluckner, Thomas Pock, Horst Bischof