71 search results - page 1 / 15 » Sparse Signal Recovery Using Markov Random Fields |
86
Voted
NIPS
2008
14 years 11 months ago
2008
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
112
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ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
112
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TSP
2010
14 years 4 months ago
2010
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
124
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ICCV
2009
IEEE
16 years 2 months ago
2009
IEEE
Partially occluded faces are common in many applications
of face recognition. While algorithms based on sparse
representation have demonstrated promising results, they
achieve t...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
Stochastic image modeling based on conventional Markov random fields is extensively discussed in the literature. A new stochastic image model based on Markov random fields is intr...