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Calibration Models and System Development for Compressive Sensing with Micromirror Arrays

Profeta, Rebecca L.
http://orcid.org/0000-0002-8253-3243
http://rave.ohiolink.edu/etdc/view?acc_num=wright15160282553897

Abstract Details

2017, Master of Science in Electrical Engineering (MSEE), Wright State University, Electrical Engineering.
Compressive sensing (CS) is an active research field focused on finding solutions to sparse linear inverse problems, i.e. estimating a signal using fewer linear measurements than there are unknowns. The assumption of signal sparsity makes solutions to this otherwise ill-posed problem possible and has lead to a number of technological innovations such as smaller and less expensive cameras that capture high resolution imagery, low-power radar systems, and accelerated MRI scanners. In this thesis, we present the development of a hardware CS imaging system using a Digital Micromirror Device (DMD) providing spatial light modulation via an array of micromirrors that can be programmatically controlled to produce automated measurements. Additionally, we develop a number of new DMD-specific calibration models intended to capture the physical attributes of micromirrors and the end-to-end data collection system. Algorithms are derived to fit the calibration models from training data, and resultant CS reconstructions demonstrate a substantial reduction in image estimation error while reducing the number of required measurements by fifty percent, relative to current baseline calibration methods.
Joshua Ash, Ph.D. (Advisor)
Arnab Shaw, Ph.D. (Committee Member)
Vince Velten, Ph.D. (Committee Member)
81 p.
Electrical Engineering
Compressive Sensing; Digital Mircromirror Device; Calibration; Bayesian Compressive Sensing; Relevance Vector Machine

Recommended Citations

Citations

  • Profeta, R. L. (2017). Calibration Models and System Development for Compressive Sensing with Micromirror Arrays [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright15160282553897

    APA Style (7th edition)

  • Profeta, Rebecca. Calibration Models and System Development for Compressive Sensing with Micromirror Arrays. 2017. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright15160282553897.

    MLA Style (8th edition)

  • Profeta, Rebecca. "Calibration Models and System Development for Compressive Sensing with Micromirror Arrays." Master's thesis, Wright State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright15160282553897

    Chicago Manual of Style (17th edition)

wright15160282553897
320
© 2017, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.