Compressive video sensors using multichannel imagers.
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2010-04-01
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Abstract
We explore the possibilities of obtaining compression in video through modified sampling strategies using multichannel imaging systems. The redundancies in video streams are exploited through compressive sampling schemes to achieve low power and low complexity video sensors. The sampling strategies as well as the associated reconstruction algorithms are discussed. These compressive sampling schemes could be implemented in the focal plane readout hardware resulting in drastic reduction in data bandwidth and computational complexity.
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Scholars@Duke
Nikos Pitsianis
David J. Brady
David Brady leads the Duke Information Spaces Project (DISP). Historically, DISP has focused on computational imaging systems, with particular emphasis on smart cameras for security, consumer, transportation and broadcast applications. Currently DISP focuses primarily on the use of artificial intelligence in camera arrays for interactive broadcasting.
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