Compressive video sensors using multichannel imagers

Mohan Shankar; Nikos P. Pitsianis; David J. Brady

doi:10.1364/AO.49.0000B9

Compressive video sensors using multichannel imagers

Mohan Shankar
, Nikos P. Pitsianis
, David J. Brady

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

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.

Original language	English (US)
Pages (from-to)	B9-B17
Journal	Applied optics
Volume	49
Issue number	10
DOIs	https://doi.org/10.1364/AO.49.0000B9
State	Published - Apr 1 2010
Externally published	Yes

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Engineering (miscellaneous)
Electrical and Electronic Engineering

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10.1364/AO.49.0000B9

Cite this

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title = "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.",

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AU - Brady, David J.

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AB - 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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Compressive video sensors using multichannel imagers

Abstract

ASJC Scopus subject areas

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