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Numerical Methods For Ill-Posed Problems With Applications

Hearn, Tristan A.
http://rave.ohiolink.edu/etdc/view?acc_num=kent1333415470

Abstract Details

2012, PHD, Kent State University, College of Arts and Sciences / Department of Mathematical Sciences.
Several new methods for object detection, denoising, and deblurring of digital images are presented. Among these are a new method for fast computation of convolution operations, a new framework for denoising via adaptive thresholding of wavelet coefficients based upon high order statistics of the residual image, and an extension of a non-iterative blind deconvolution algorithm to non-periodic boundary conditions. Each presented method is applicable to real-world problems, substantiated through extensive numerical experimentation.
Lothar Reichel, PhD (Advisor)
Jing Li, PhD (Committee Member)
Kazim Khan, PhD (Committee Member)
Arden Ruttan, PhD (Committee Member)
Robin Selinger, PhD (Committee Member)
146 p.
Applied Mathematics

Recommended Citations

Citations

  • Hearn, T. A. (2012). Numerical Methods For Ill-Posed Problems With Applications [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1333415470

    APA Style (7th edition)

  • Hearn, Tristan. Numerical Methods For Ill-Posed Problems With Applications. 2012. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1333415470.

    MLA Style (8th edition)

  • Hearn, Tristan. "Numerical Methods For Ill-Posed Problems With Applications." Doctoral dissertation, Kent State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1333415470

    Chicago Manual of Style (17th edition)

kent1333415470
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© 2012, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.