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» Compressed Sensing and Redundant Dictionaries
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ICASSP
2008
IEEE
14 years 2 months ago
Distributed compressed sensing: Sparsity models and reconstruction algorithms using annihilating filter
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
Ali Hormati, Martin Vetterli
CVPR
2009
IEEE
15 years 2 months ago
Topology Dictionary with Markov Model for 3D Video Content-Based Skimming and Description
This paper presents a novel approach to skim and describe 3D videos. 3D video is an imaging technology which consists in a stream of 3D models in motion captured by a synchronized ...
Tony Tung (Kyoto University), Takashi Matsuyama (K...
PERCOM
2010
ACM
13 years 6 months ago
Resilient image sensor networks in lossy channels using compressed sensing
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
DCC
2001
IEEE
14 years 7 months ago
LIPT: A Reversible Lossless Text Transform to Improve Compression Performance
Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv family, Dynamic Markov Compression (D...
Fauzia S. Awan, Nan Zhang 0005, Nitin Motgi, Raja ...
PAMI
2012
11 years 10 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce