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ICASSP
2009
IEEE
16 years 1 months ago
Fast bayesian compressive sensing using Laplace priors
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
DCC
2011
IEEE
15 years 1 months ago
Residual Reconstruction for Block-Based Compressed Sensing of Video
A simple block-based compressed-sensing reconstruction for still images is adapted to video. Incorporating reconstruction from a residual arising from motion estimation and compen...
Sungkwang Mun, James E. Fowler
CORR
2010
Springer
172views Education» more  CORR 2010»
15 years 6 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang
CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 6 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
CORR
2011
Springer
282views Education» more  CORR 2011»
15 years 1 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