Abstract
On the Relation between Constraint Regularization, Level Sets, and Shape Optimization
Otmar Scherzer
Leopold-Franzens Universität Innsbruck
We consider regularization methods based on the coupling of Tikhonov regularization and projection strategies. From the resulting constraint regularization method we obtain level set methods in a straight forward way.
Moreover, we show that this approach links the areas of asymptotic regularization to inverse problems theory, scale-space theory to computer vision, level set methods, and shape optimization.
Finally we present a convergence analysis for level set regularization.
Moreover, we show that this approach links the areas of asymptotic regularization to inverse problems theory, scale-space theory to computer vision, level set methods, and shape optimization.
Finally we present a convergence analysis for level set regularization.
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