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» Sparse Image Reconstruction using Sparse Priors
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ICASSP
2011
IEEE
14 years 7 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
MICCAI
2008
Springer
16 years 5 months ago
A Distributed Spatio-temporal EEG/MEG Inverse Solver
We propose a novel 1 2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard 1-norm inverse solver, the proposed sparse distributed inverse solve...
Wanmei Ou, Polina Golland, Matti Hämäl&a...
ICVGIP
2008
15 years 5 months ago
Monocular Depth by Nonlinear Diffusion
Following the phenomenological approach of gestaltists, sparse monocular depth cues such as T- and X-junctions and the local convexity are crucial to identify the shape and depth ...
Jean-Michel Morel, Philippe Salembier
SGP
2003
15 years 5 months ago
Global Conformal Parameterization
We solve the problem of computing global conformal parameterizations for surfaces with nontrivial topologies. The parameterization is global in the sense that it preserves the con...
Xianfeng Gu, Shing-Tung Yau
CISS
2008
IEEE
15 years 10 months ago
Sparsity in MRI RF excitation pulse design
—Magnetic resonance imaging (MRI) may be viewed as a two-stage experiment that yields a non-invasive spatial mapping of hydrogen nuclei in living subjects. Nuclear spins within a...
Adam C. Zelinski, Vivek K. Goyal, Elfar Adalsteins...