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Computational optical imaging: Appli...

Lee, Dennis Joseph.

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Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography./
Author:	Lee, Dennis Joseph.
Description:	91 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
Contained By:	Dissertation Abstracts International76-12B(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3719404
ISBN:	9781321997453

Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography.
Lee, Dennis Joseph.

Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography. - 91 p.

Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.

Thesis (Ph.D.)--Purdue University, 2015.

Computational imaging has become an important field, as a merger of both algorithms and physical experiments. In the realm of microscopy and optical imaging, an important application is the problem of improving resolution, which is bounded by wavelength and numerical aperture according to the classic diffraction limit. We will investigate the resolution enhancement of phase objects such as transparent biological cells. One key challenge is how to measure phase experimentally. Standard interferometric techniques have the drawback of being sensitive to environmental vibrations and temperature fluctuations, and they use a reference arm which requires more space and cost. Non-holographic methods provide a way to overcome these disadvantages. Another challenge is how to reconstruct phase and amplitude from a digital hologram. The typical method of applying a filter in the frequency domain is limited by finite filter size. Optimization approaches offer a solution to this problem.

ISBN: 9781321997453Subjects--Topical Terms:

649834
Electrical engineering.

Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography.
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020 $a 9781321997453
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100 1 $a Lee, Dennis Joseph. $3 3185925
245 1 0 $a Computational optical imaging: Applications in synthetic aperture imaging, phase retrieval, and digital holography.
300 $a 91 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-12(E), Section: B.
500 $a Adviser: Andrew M. Weiner.
502 $a Thesis (Ph.D.)--Purdue University, 2015.
520 $a Computational imaging has become an important field, as a merger of both algorithms and physical experiments. In the realm of microscopy and optical imaging, an important application is the problem of improving resolution, which is bounded by wavelength and numerical aperture according to the classic diffraction limit. We will investigate the resolution enhancement of phase objects such as transparent biological cells. One key challenge is how to measure phase experimentally. Standard interferometric techniques have the drawback of being sensitive to environmental vibrations and temperature fluctuations, and they use a reference arm which requires more space and cost. Non-holographic methods provide a way to overcome these disadvantages. Another challenge is how to reconstruct phase and amplitude from a digital hologram. The typical method of applying a filter in the frequency domain is limited by finite filter size. Optimization approaches offer a solution to this problem.
520 $a The work presented here spans three main aspects of phase imaging microscopy including synthetic aperture imaging, phase retrieval, and digital holography. We develop a non-holographic microscope that uses off-axis illumination for resolution enhancement and demonstrate the first experimental measurements of referenceless phase retrieval at multiple angles. We implement a synthetic aperture microscope using an electrically tunable lens to defocus images, which avoids the need to mechanically move a camera on a translation stage. Finally, we improve the reconstruction of images from a digital hologram based on an iterative algorithm that alternatively updates amplitude and phase.
590 $a School code: 0183.
650 4 $a Electrical engineering. $3 649834
650 4 $a Engineering. $3 586835
650 4 $a Optics. $3 517925
690 $a 0544
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710 2 $a Purdue University. $b Electrical and Computer Engineering. $3 1018497
773 0 $t Dissertation Abstracts International $g 76-12B(E).
790 $a 0183
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3719404