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research:tomography:start [2015/03/22 20:07]
aneufeld
research:tomography:start [2015/03/22 20:07] (current)
aneufeld
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     *  **__Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections__** *      *  **__Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections__** * 
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 Compared to the well known Nyquist-Shannon sampling theorem, which allows a signal to be accurately reconstructed only if there are twice more measurements available than the sampling rate at which the signal was acquired, compressive sensing (CS) has been advocated as a sparsity promoting approach, able to obtain accurate reconstructions from a few linear, but random and non-adaptive measurements. Compared to the well known Nyquist-Shannon sampling theorem, which allows a signal to be accurately reconstructed only if there are twice more measurements available than the sampling rate at which the signal was acquired, compressive sensing (CS) has been advocated as a sparsity promoting approach, able to obtain accurate reconstructions from a few linear, but random and non-adaptive measurements.