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Sampling and signal estimation in co...

Shankar, Mohan.

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Sampling and signal estimation in computational optical sensors.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Sampling and signal estimation in computational optical sensors./
作者:	Shankar, Mohan.
面頁冊數:	140 p.
附註:	Adviser: David J. Brady.
Contained By:	Dissertation Abstracts International68-11B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3284298
ISBN:	9780549296027

Sampling and signal estimation in computational optical sensors.
Shankar, Mohan.

Sampling and signal estimation in computational optical sensors. - 140 p.

Adviser: David J. Brady.

Thesis (Ph.D.)--Duke University, 2007.

Computational sensing utilizes non-conventional sampling mechanisms along with processing algorithms for accomplishing various sensing tasks. It provides additional flexibility in designing imaging or spectroscopic systems. This dissertation analyzes sampling and signal estimation techniques through three computational sensing systems to accomplish specific tasks. The first is thin long-wave infrared imaging systems through multichannel sampling. Significant reduction in optical system thickness is obtained over a conventional system by modifying conventional sampling mechanisms and applying reconstruction algorithms. In addition, an information theoretic analysis of sampling in conventional as well as multichannel imaging systems is also performed. The feasibility of performing multichannel sampling for imaging is demonstrated using an information theoretic metric. The second system is an application of the multichannel system for the design of compressive low-power video sensors. Two sampling schemes have been demonstrated that utilize spatial as well as temporal aliasing. The third system is a novel computational spectroscopic system for detecting chemicals that utilizes the surface plasmon resonances to encode information about the chemicals that are tested.

ISBN: 9780549296027Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Sampling and signal estimation in computational optical sensors.
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502 $a Thesis (Ph.D.)--Duke University, 2007.
520 $a Computational sensing utilizes non-conventional sampling mechanisms along with processing algorithms for accomplishing various sensing tasks. It provides additional flexibility in designing imaging or spectroscopic systems. This dissertation analyzes sampling and signal estimation techniques through three computational sensing systems to accomplish specific tasks. The first is thin long-wave infrared imaging systems through multichannel sampling. Significant reduction in optical system thickness is obtained over a conventional system by modifying conventional sampling mechanisms and applying reconstruction algorithms. In addition, an information theoretic analysis of sampling in conventional as well as multichannel imaging systems is also performed. The feasibility of performing multichannel sampling for imaging is demonstrated using an information theoretic metric. The second system is an application of the multichannel system for the design of compressive low-power video sensors. Two sampling schemes have been demonstrated that utilize spatial as well as temporal aliasing. The third system is a novel computational spectroscopic system for detecting chemicals that utilizes the surface plasmon resonances to encode information about the chemicals that are tested.
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