Modeling, Analysis, and Implementation of Finite Difference Schemes for Nonlinear Diffusion with Applications to Image Processing

dc.contributor.advisorSeshaiyer, Padmanabhan
dc.contributor.authorFranklin, Armelle S.
dc.creatorFranklin, Armelle S.
dc.date2013-05-02
dc.date.accessioned2013-08-13T17:50:41Z
dc.date.availableNO_RESTRICTION
dc.date.available2013-08-13T17:50:41Z
dc.date.issued2013-08-13
dc.description.abstractThis thesis proposes to model, analyze and implement a nonlinear diffusion model problem for reduction in noise and speckle in image processing applications. Specifically, the Perona-Malik model equation that is widely studied in the image processing community is implemented via explicit and implicit finite difference algorithms. The solution methodology converts discrete image data onto a finer non-uniform grid space via interpolation techniques and applies the proposed numerical algorithms to reduce noise. These numerical algorithms are investigated analytically and computationally for appropriate choices of nonlinear diffusion coefficient functions. We derived conditions for stability and convergence of the proposed numerical algorithms. Numerical experiments are presented on benchmark problems that show the robustness and reliability of the proposed numerical schemes.
dc.identifier.urihttps://hdl.handle.net/1920/8293
dc.language.isoen
dc.subjectFinite difference
dc.subjectImage processing
dc.subjectPerona-Malik
dc.subjectNonlinear diffusion
dc.subjectNoise reduction
dc.subjectSpeckle
dc.titleModeling, Analysis, and Implementation of Finite Difference Schemes for Nonlinear Diffusion with Applications to Image Processing
dc.typeThesis
thesis.degree.disciplineMathematics
thesis.degree.grantorGeorge Mason University
thesis.degree.levelMaster's
thesis.degree.nameMaster of Science in Mathematics

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