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A Conditional Generative Adversarial Network Demosaicing Strategy for Division of Focal Plane Polarimeters

Sargent, Garrett Craig
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1606050550958383

Abstract Details

2020, Doctor of Philosophy (Ph.D.), University of Dayton, Electrical and Computer Engineering.
Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2x2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial network (cGAN) approach to the microgrid demosaicing problem. We evaluate the performance of our approach against full-resolution division-of-time polarimeter data as well as compare against both traditional and recent microgrid demosaicing methods. We apply these demosaicing strategies to data from both real and simulated visible microgrid imagery and provide an objective criteria for evaluating their performance. We demonstrate that the proposed cGAN approach results in estimated Stokes imagery that is comparable to full-resolution ground truth imagery from both a quantitative and qualitative perspective.
Bradley Ratliff, PhD (Advisor)
Vijayan Asari, PhD (Advisor)
Ilya Lipkin, PhD (Committee Member)
Eric Balster, PhD (Committee Member)
70 p.
Electrical Engineering
deep learning; GAN; demosaicing; polarimetric imaging; microgrid polarimeters

Recommended Citations

Citations

  • Sargent, G. C. (2020). A Conditional Generative Adversarial Network Demosaicing Strategy for Division of Focal Plane Polarimeters [Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1606050550958383

    APA Style (7th edition)

  • Sargent, Garrett. A Conditional Generative Adversarial Network Demosaicing Strategy for Division of Focal Plane Polarimeters. 2020. University of Dayton, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1606050550958383.

    MLA Style (8th edition)

  • Sargent, Garrett. "A Conditional Generative Adversarial Network Demosaicing Strategy for Division of Focal Plane Polarimeters." Doctoral dissertation, University of Dayton, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1606050550958383

    Chicago Manual of Style (17th edition)

dayton1606050550958383
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© 2020, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.