東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Applications of Non-Traditional Meas...

Treeaporn, Vicha.

FindBook

Google Book

Amazon

博客來

Applications of Non-Traditional Measurements for Computational Imaging.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applications of Non-Traditional Measurements for Computational Imaging./
作者:	Treeaporn, Vicha.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	119 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Contained By:	Dissertation Abstracts International78-10B(E).
標題:	Electrical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10276817
ISBN:	9781369804294

Applications of Non-Traditional Measurements for Computational Imaging.
Treeaporn, Vicha.

Applications of Non-Traditional Measurements for Computational Imaging. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 119 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.

Thesis (Ph.D.)--The University of Arizona, 2017.

Imaging systems play an important role in many diverse applications. Requirements for these applications, however, can lead to complex or sub-optimal designs. Traditionally, imaging systems are designed to yield a visually pleasing representation, or "pretty picture", of the scene or object. Often this is because a human operator is viewing the acquired image to perform a specific task. With digital computers increasingly being used for automation, a large number of algorithms have been designed to accept as input a pretty picture. This isomorphic representation however is neither necessary nor optimal for tasks such as data compression, transmission, pattern recognition or classification. This disconnect between optical measurement and post processing for the final system outcome has motivated an interest in computational imaging (CI). In a CI system the optical sub-system and post-processing sub-system is jointly designed to optimize system performance for a specific task. In these hybrid imagers, the measured image may no longer be a pretty picture but rather an intermediate non-traditional measurement. In this work, applications of non-traditional measurements are considered for computational imaging. Two systems for an image reconstruction task are studied and one system for a detection task is investigated. First, a CI system to extend the field of view is analyzed and an experimental prototype demonstrated. This prototype validates the simulation study and is designed to yield a 3x field of view improvement relative to a conventional imager. Second, a CI system to acquire time-varying natural scenes, i.e. video, is developed. A candidate system using 8 x 8 x16 spatiotemporal blocks yields about 292x compression compared to a conventional imager. Candidate electro-optical architectures, including charge-domain processing, to implement this approach are also discussed. Lastly, a CI system with x-ray pencil beam illumination is investigated for a detection task where system performance is quantified using an information-theoretic metric.

ISBN: 9781369804294Subjects--Topical Terms:

649834
Electrical engineering.

Applications of Non-Traditional Measurements for Computational Imaging.
LDR:03023nmm a2200301 4500 001 2166112
005 20181203094030.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9781369804294
035 $a (MiAaPQ)AAI10276817
035 $a (MiAaPQ)arizona:15435
035 $a AAI10276817
040 $a MiAaPQ $c MiAaPQ
100 1 $a Treeaporn, Vicha. $3 3354217
245 1 0 $a Applications of Non-Traditional Measurements for Computational Imaging.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 119 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
500 $a Adviser: Mark A. Neifeld.
502 $a Thesis (Ph.D.)--The University of Arizona, 2017.
520 $a Imaging systems play an important role in many diverse applications. Requirements for these applications, however, can lead to complex or sub-optimal designs. Traditionally, imaging systems are designed to yield a visually pleasing representation, or "pretty picture", of the scene or object. Often this is because a human operator is viewing the acquired image to perform a specific task. With digital computers increasingly being used for automation, a large number of algorithms have been designed to accept as input a pretty picture. This isomorphic representation however is neither necessary nor optimal for tasks such as data compression, transmission, pattern recognition or classification. This disconnect between optical measurement and post processing for the final system outcome has motivated an interest in computational imaging (CI). In a CI system the optical sub-system and post-processing sub-system is jointly designed to optimize system performance for a specific task. In these hybrid imagers, the measured image may no longer be a pretty picture but rather an intermediate non-traditional measurement. In this work, applications of non-traditional measurements are considered for computational imaging. Two systems for an image reconstruction task are studied and one system for a detection task is investigated. First, a CI system to extend the field of view is analyzed and an experimental prototype demonstrated. This prototype validates the simulation study and is designed to yield a 3x field of view improvement relative to a conventional imager. Second, a CI system to acquire time-varying natural scenes, i.e. video, is developed. A candidate system using 8 x 8 x16 spatiotemporal blocks yields about 292x compression compared to a conventional imager. Candidate electro-optical architectures, including charge-domain processing, to implement this approach are also discussed. Lastly, a CI system with x-ray pencil beam illumination is investigated for a detection task where system performance is quantified using an information-theoretic metric.
590 $a School code: 0009.
650 4 $a Electrical engineering. $3 649834
650 4 $a Optics. $3 517925
690 $a 0544
690 $a 0752
710 2 $a The University of Arizona. $b Electrical & Computer Engineering. $3 1018545
773 0 $t Dissertation Abstracts International $g 78-10B(E).
790 $a 0009
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10276817