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» On sparse signal representations
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SIAMIS
2008
211views more  SIAMIS 2008»
14 years 9 months ago
Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
Modeling signals by sparse and redundant representations has been drawing considerable attention in recent years. Coupled with the ability to train the dictionary using signal exam...
Michal Aharon, Michael Elad
ICASSP
2010
IEEE
14 years 8 months ago
Human detection in images via L1-norm Minimization Learning
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Ran Xu, Baochang Zhang, Qixiang Ye, Jianbin Jiao
87
Voted
ICIP
2008
IEEE
15 years 4 months ago
Atomic decomposition dedicated to AVC and spatial SVC prediction
In this work, we propose the use of sparse signal representation techniques to solve the problem of closed-loop spatial image prediction. The reconstruction of signal in the block...
Aurelie Martin, Jean-Jacques Fuchs, Christine Guil...
ICIP
2004
IEEE
15 years 11 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
CVPR
2010
IEEE
15 years 2 months ago
Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Shenghua Gao, Wai-Hung Tsang, Liang-Tien Chia, Pei...