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DCC
2008
IEEE
16 years 2 months ago
Compressive-Projection Principal Component Analysis for the Compression of Hyperspectral Signatures
A method is proposed for the compression of hyperspectral signature vectors on severely resourceconstrained encoding platforms. The proposed technique, compressive-projection prin...
James E. Fowler
108
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ICASSP
2008
IEEE
15 years 9 months ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
153
Voted
CORR
2011
Springer
282views Education» more  CORR 2011»
14 years 10 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
CORR
2008
Springer
178views Education» more  CORR 2008»
15 years 3 months ago
Model-Based Compressive Sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...
ICIP
2008
IEEE
15 years 9 months ago
Compressed sensing for multi-view tracking and 3-D voxel reconstruction
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...
Dikpal Reddy, Aswin C. Sankaranarayanan, Volkan Ce...