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|a 10.1109/TIP.2015.2474697
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|a eng
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|a Goldstein, Tom
|e verfasserin
|4 aut
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|a The STOne Transform
|b Multi-Resolution Image Enhancement and Compressive Video
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|c 2015
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|a Text
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|a ƒaComputermedien
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|a Date Completed 03.02.2016
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|a Date Revised 27.01.2016
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Compressive sensing enables the reconstruction of high-resolution signals from under-sampled data. While the compressive methods simplify data acquisition, they require the solution of difficult recovery problems to make use of the resulting measurements. This paper presents a new sensing framework that combines the advantages of both the conventional and the compressive sensing. Using the proposed sum-to-one transform, the measurements can be reconstructed instantly at the Nyquist rates at any power-of-two resolution. The same data can then be enhanced to higher resolutions using the compressive methods that leverage sparsity to beat the Nyquist limit. The availability of a fast direct reconstruction enables the compressive measurements to be processed on small embedded devices. We demonstrate this by constructing a real-time compressive video camera
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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|a Xu, Lina
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| 700 |
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|a Kelly, Kevin F
|e verfasserin
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| 700 |
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|a Baraniuk, Richard
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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|g 24(2015), 12 vom: 23. Dez., Seite 5581-93
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