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A Graph Framework for Manifold-Valued Data
2018
SIAM Journal of Imaging Sciences
Graph-based methods have been proposed as a unified framework for discrete calculus of local and nonlocal image processing methods in the recent years. In order to translate variational models and partial differential equations to a graph, certain operators have been investigated and successfully applied to real-world applications involving graph models. So far the graph framework has been limited to real- and vector-valued functions on Euclidean domains. In this paper we generalize this model
doi:10.1137/17m1118567
fatcat:eaqed7qypjb4ffmwdd3jlghewi