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TSP
2010
13 years 2 months ago
Coherence-based performance guarantees for estimating a sparse vector under random noise
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 +w, where w represents white Gaussian noise and A is a given determinis...
Zvika Ben-Haim, Yonina C. Eldar, Michael Elad
ICML
2010
IEEE
13 years 8 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
TIP
2010
255views more  TIP 2010»
13 years 2 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
CVPR
2006
IEEE
14 years 9 months ago
Image Denoising Via Learned Dictionaries and Sparse representation
We address the image denoising problem, where zeromean white and homogeneous Gaussian additive noise should be removed from a given image. The approach taken is based on sparse an...
Michael Elad, Michal Aharon
ICIP
2004
IEEE
14 years 9 months ago
Learning structured dictionaries for image representation
The dictionary approach to signal and image processing has been massively investigated in the last two decades, proving very attractive for a wide range of applications. The effec...
Gianluca Monaci, Pierre Vandergheynst