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Mulit-Resolution Aitchison Geometry Image Denoising for Low-Light Photography

Miller, Sarah Victoria
http://orcid.org/0000-0001-7593-8624
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1596444315236623

Abstract Details

2020, Master of Science in Electrical Engineering, University of Dayton, Electrical and Computer Engineering.
In low-photon imaging regime, noise in image sensors are dominated by shot noise, best modeled statistically as Poisson. In this work, we show that the Poisson likelihood function is very well matched with the Bayesian estimation of the "difference of log of contrast of pixel intensities". More specifically, our work takes root in statistical compositional data analysis, whereby we reinterpret the Aitchison geometry as a multiresolution analysis in log-pixel domain. We demonstrate that the difference-log-contrast has wavelet-like properties that correspond well with human visual system, while being robust to illumination variations. We derive a denoising technique based on an approximate conjugate prior for the latent Aitchison variable that gives rise to an explicit minimum mean squared error estimation. The resulting denoising techniques preserves image contrast details that are arguably more meaningful to human vision than the pixel intensity values themselves.
Keigo Hirakawa, Ph.D. (Advisor)
Brad Ratliff, Ph.D. (Committee Member)
Vijayan Asari, Ph.D. (Committee Member)
43 p.
Electrical Engineering
Image denoising, Poisson, low light imaging, Aitchison geometry

Recommended Citations

Citations

  • Miller, S. V. (2020). Mulit-Resolution Aitchison Geometry Image Denoising for Low-Light Photography [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1596444315236623

    APA Style (7th edition)

  • Miller, Sarah. Mulit-Resolution Aitchison Geometry Image Denoising for Low-Light Photography. 2020. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1596444315236623.

    MLA Style (8th edition)

  • Miller, Sarah. "Mulit-Resolution Aitchison Geometry Image Denoising for Low-Light Photography." Master's thesis, University of Dayton, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1596444315236623

    Chicago Manual of Style (17th edition)

dayton1596444315236623
246
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This open access ETD is published by University of Dayton and OhioLINK.