Titlebook: Scale Space and Variational Methods in Computer Vision; 7th International Co Jan Lellmann,Martin Burger,Jan Modersitzki Conference proceedi

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Time Discrete Geodesics in Deep Feature Spaces for Image Morphingproposed by Trouvé, Younes and coworkers is image metamorphosis. Here, the space of images is endowed with a Riemannian metric that separately quantifies the contributions due to transport and image intensity variations along a transport path. Geodesic curves in this Riemannian space of images give

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Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphsed .-norms converge to these extensions as .. Further, we examine the relation between minimal Lipschitz extensions and iterated weighted midrange filters and address their connection to .-Laplacians for scalar-valued functions. A convergence proof for an iterative algorithm proposed in [.] for finding the zero of the .-Laplacian is given.

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Conference proceedings 2019were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction;  scale-space methods; segmentation and labeling; and variational methods. .

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