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Publication 91

A Few Remarks on Variational Models for Denoising

Authors:

Rustum Choksi
Department of Mathematics and Statistics
McGill University, Montreal, Canada


CMUIrene Fonseca
Department of Mathematical Sciences
Carnegie Mellon University
Pittsburgh, PA 15213


CMUBarbara Zwicknagl
Department of Mathematical Sciences
Carnegie Mellon University
Pittsburgh, PA 15213


Abstract:
A class of variational models for image and signal denoising is considered. These models are based on the minimization of energy functionals consisting of a fidelity term together with higher-order regularization. In addition to the choices of function spaces to measure fidelity and impose regularization, different scaling exponents appear. The relationship between certain desirable properties for these models and the choice of function spaces and scaling exponents is addressed. In particular, stability of these models is discussed with respect to deterministic noise perturbations, captured via oscillatory sequences converging weakly to zero.
Get the paper in its entirety
12-CNA-008.pdf

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