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Convex Color Image Segmentation with Optimal Transport Distances
March 06, 2015 Β· Declared Dead Β· π Scale Space and Variational Methods in Computer Vision
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Authors
Julien Rabin, Nicolas Papadakis
arXiv ID
1503.01986
Category
cs.CV: Computer Vision
Citations
65
Venue
Scale Space and Variational Methods in Computer Vision
Last Checked
5 months ago
Abstract
This work is about the use of regularized optimal-transport distances for convex, histogram-based image segmentation. In the considered framework, fixed exemplar histograms define a prior on the statistical features of the two regions in competition. In this paper, we investigate the use of various transport-based cost functions as discrepancy measures and rely on a primal-dual algorithm to solve the obtained convex optimization problem.
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