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CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 7 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
PAMI
2011
13 years 2 months ago
Coded Strobing Photography: Compressive Sensing of High Speed Periodic Videos
—We show that, via temporal modulation, one can observe and capture a high-speed periodic video well beyond the abilities of a low-frame-rate camera. By strobing the exposure wit...
Ashok Veeraraghavan, Dikpal Reddy, Ramesh Raskar
CORR
2011
Springer
282views Education» more  CORR 2011»
13 years 2 months ago
Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising
We propose and analyze an extremely fast, efficient and simple method for solving the problem: min{ u 1 :Au=f,u∈Rn }. This method was first described in [1], with more details i...
Stanley Osher, Yu Mao, Bin Dong, Wotao Yin
TSP
2008
101views more  TSP 2008»
13 years 7 months ago
Bayesian Compressive Sensing
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be recons...
Shihao Ji, Ya Xue, Lawrence Carin
TIP
2010
127views more  TIP 2010»
13 years 5 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...