Fast algorithms for phase diversity-based blind deconvolution

Curtis R. Vogel; Tony F. Chan; Robert J. Plemmons

doi:10.1117/12.321720

Fast algorithms for phase diversity-based blind deconvolution

Curtis R. Vogel, Tony F. Chan, Robert J. Plemmons

Research output: Contribution to journal › Conference article › peer-review

72 Scopus citations

Abstract

Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.

Original language	English (US)
Pages (from-to)	994-1005
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3353
DOIs	https://doi.org/10.1117/12.321720
State	Published - 1998
Externally published	Yes
Event	Adaptive Optical System Technologies - Kona, HI, United States Duration: Mar 23 1998 → Mar 23 1998

Keywords

Blind deconvolution
Phase diversity
Phase retrieval
Quasi-Newton methods

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.321720

Cite this

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title = "Fast algorithms for phase diversity-based blind deconvolution",

abstract = "Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.",

keywords = "Blind deconvolution, Phase diversity, Phase retrieval, Quasi-Newton methods",

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year = "1998",

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T1 - Fast algorithms for phase diversity-based blind deconvolution

AU - Vogel, Curtis R.

AU - Chan, Tony F.

AU - Plemmons, Robert J.

PY - 1998

Y1 - 1998

N2 - Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.

AB - Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.

KW - Blind deconvolution

KW - Phase diversity

KW - Phase retrieval

KW - Quasi-Newton methods

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U2 - 10.1117/12.321720

DO - 10.1117/12.321720

M3 - Conference article

AN - SCOPUS:0032284527

SN - 0277-786X

VL - 3353

SP - 994

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JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Adaptive Optical System Technologies

Y2 - 23 March 1998 through 23 March 1998

ER -

Fast algorithms for phase diversity-based blind deconvolution

Abstract

Keywords

ASJC Scopus subject areas

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