Browse by Subject "dictionary learning"

  • Ravishankar, Saiprasad (2014-12-05)
    The sparsity of signals and images in a certain transform domain or dictionary has been exploited in many applications in signal processing, image processing, and medical imaging. Analytical sparsifying transforms such as ...

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  • Wang, Zhaowen (2015-01-21)
    Natural images have the intrinsic property that they can be sparsely represented as a linear combination of a very small number of atomic signals from a complete basis or an overcomplete dictionary. This sparse representation ...

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  • Ravishankar, Saiprasad (2011-01-21)
    Compressed sensing (CS) utilizes the sparsity of MR images to enable accurate reconstruction from undersampled k-space data. Recent CS methods have employed analytical sparsifying transforms such as wavelets, curvelets, ...

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