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ISBI
2009
IEEE
15 years 11 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
CORR
2010
Springer
275views Education» more  CORR 2010»
15 years 4 months ago
Dictionary Optimization for Block-Sparse Representations
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
CORR
2011
Springer
191views Education» more  CORR 2011»
14 years 11 months ago
A Message-Passing Receiver for BICM-OFDM over Unknown Clustered-Sparse Channels
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...
Philip Schniter
PAMI
2011
14 years 11 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
ICIP
2006
IEEE
16 years 5 months ago
Parameter Estimation in Bayesian Reconstruction of Multispectral Images using Super Resolution Techniques
In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of...
Rafael Molina, Miguel Vega, Javier Mateos, Aggelos...