Compressive video sensors using multichannel imagers.
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.
Type
Journal articlePermalink
https://hdl.handle.net/10161/4207Collections
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Show full item recordScholars@Duke
David J. Brady
Michael J. Fitzpatrick Distinguished Professor Emeritus of Photonics
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.
Nikos Pitsianis
Adjunct Associate Professor of Computer Science
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