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ICASSP
2010
IEEE
14 years 6 months ago
Using reed-muller sequences as deterministic compressed sensing matrices for image reconstruction
An image reconstruction algorithm using compressed sensing (CS) with deterministic matrices of second-order ReedMuller (RM) sequences is introduced. The 1D algorithm of Howard et ...
Kangyu Ni, Somantika Datta, Prasun Mahanti, Svetla...
ISBI
2009
IEEE
15 years 6 months ago
Fast Algorithms for Nonconvex Compressive Sensing: MRI Reconstruction from Very Few Data
Compressive sensing is the reconstruction of sparse images or signals from very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can ...
Rick Chartrand
ICIP
2008
IEEE
15 years 5 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...
ICASSP
2011
IEEE
14 years 2 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes
CIMAGING
2009
192views Hardware» more  CIMAGING 2009»
15 years 8 days ago
Compressive coded aperture imaging
Nonlinear image reconstruction based upon sparse representations of images has recently received widespread attention with the emerging framework of compressed sensing (CS). This ...
Roummel F. Marcia, Zachary T. Harmany, Rebecca Wil...