Compressive Sensing via Low-Rank Gaussian Mixture Models

We develop a new compressive sensing (CS) inversion algorithm by utilizing the Gaussian mixture model (GMM). While the compressive sensing is performed globally on the entire image as implemented in our lensless camera, a low-rank GMM is imposed on the local image patches. This low-rank GMM is deriv...

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Bibliographische Detailangaben

Hauptverfasser:	Yuan, Xin, Jiang, Hong, Huang, Gang, Wilford, Paul A
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Applications Statistics - Machine Learning
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