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Proceedings Paper

Progressive compressive imager
Author(s): Sergei Evladov; Ofer Levi; Adrian Stern
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Paper Abstract

We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

Paper Details

Date Published: 8 June 2012
PDF: 6 pages
Proc. SPIE 8365, Compressive Sensing, 83650I (8 June 2012); doi: 10.1117/12.920394
Show Author Affiliations
Sergei Evladov, Ben-Gurion Univ. of the Negev (Israel)
Ofer Levi, Ben-Gurion Univ. of the Negev (Israel)
Adrian Stern, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 8365:
Compressive Sensing
Fauzia Ahmad, Editor(s)

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