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Blind Full Reference Quality Assessment of Poisson Image Denoising

Zhang, Chen
http://orcid.org/0000-0001-8556-0186
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398875743

Abstract Details

2014, Master of Science (M.S.), University of Dayton, Electrical Engineering.
The distribution of real camera sensor data is well approximated by Poisson, and the estimation of the light intensity signal from the Poisson count data plays a prominent role in digital imaging. It is highly desirable for imaging devices to carry the ability to assess the performance of Poisson image restoration. Drawing on a new category of image quality assessment called corrupted reference image quality assessment (CR-QA), we develop a computational technique for predicting the quality score of the popular structural similarity index (SSIM) without having the direct access to the ideal reference image. We verified via simulation that the CR-SSIM scores indeed agrees with the full reference scores; and the visually optimal denoising experiments performed on real camera sensor data give credibility to the impact CR-QA has on real imaging systems.
Keigo Hirakawa (Advisor)
Russell Hardie (Committee Member)
Raul Ordonez (Committee Member)
41 p.
Electrical Engineering
Image denoising, image quality assessment

Recommended Citations

Citations

  • Zhang, C. (2014). Blind Full Reference Quality Assessment of Poisson Image Denoising [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398875743

    APA Style (7th edition)

  • Zhang, Chen. Blind Full Reference Quality Assessment of Poisson Image Denoising. 2014. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398875743.

    MLA Style (8th edition)

  • Zhang, Chen. "Blind Full Reference Quality Assessment of Poisson Image Denoising." Master's thesis, University of Dayton, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1398875743

    Chicago Manual of Style (17th edition)

dayton1398875743
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© 2014, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.