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Proceedings Paper

Spatio-temporal sampling for video
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Paper Abstract

With this work we propose spatio-temporal sampling strategies for video using a lenslet array computational imaging system and explore the opportunities and challenges in the design of compressive video sensors and corresponding processing algorithms. The redundancies in video streams are exploited by (a) sampling the sub-apertures of a multichannel (TOMBO) camera, and (b) by the computational reconstruction to achieve low power and low complexity video sensors. A spatial and a spatio-temporal sampling strategy are considered, taking into account the feasibility for implementation in the focal-plane readout hardware. The algorithms used to reconstruct the video frames from measurements are also presented.

Paper Details

Date Published: 5 September 2008
PDF: 8 pages
Proc. SPIE 7076, Image Reconstruction from Incomplete Data V, 707604 (5 September 2008); doi: 10.1117/12.795753
Show Author Affiliations
Mohan Shankar, Duke Univ. (United States)
Nikos P. Pitsianis, Duke Univ. (United States)
Aristotle Univ. (Greece)
David Brady, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 7076:
Image Reconstruction from Incomplete Data V
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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