作者: Nicolas Bonneel , Julien Rabin , Gabriel Peyré , Hanspeter Pfister
DOI: 10.1007/S10851-014-0506-3
关键词: Image processing 、 Convex optimization 、 Applied mathematics 、 Space (mathematics) 、 Discrete radon transform 、 Optimization problem 、 Mixing (mathematics) 、 Mathematical optimization 、 Radon 、 Radon transform 、 Mathematics
摘要: This article details two approaches to compute barycenters of measures using 1-D Wasserstein distances along radial projections the input measures. The first method makes use Radon transform measures, and second is solution a convex optimization problem over space We show several properties these explain their relationship. numerical approximation schemes based on discrete resolution non-convex problem. explore respective merits drawbacks each approach applications image processing problems: color transfer texture mixing.