Regularizing Image Intensity Transformations Using the Wasserstein Metric

Summary, in English

In this paper we direct our attention to the problem of discretization effects in intensity transformations of images. We propose to use the Wasserstein metric (also known as the Earth mover distance) to bootstrap the transformation process. The Wasserstein metric gives a mapping between gray levels that we use to direct our image mapping. In order to spatially regularize the image mapping we apply anisotropic filtering and use this to steer our mapping. We describe a general framework for intensity transformation, and investigate the application of our method on a number of special problems, namely histogram equalization, color transfer and bit depth expansion. We have tested our algorithms on real images, and we show that we get state-of-the-art results.

• Författare: Magnus Oskarsson
• Redaktör: Rasmus Paulsen; Kim Pedersen
• Avdelning/ar: Matematik LTH; Mathematical Imaging Group; ELLIIT: the Linköping-Lund initiative on IT and mobile communication; eSSENCE: The e-Science Collaboration
• Publiceringsår: 2015
• Språk: Engelska
• Sidor: 275-286
• Publikation/Tidskrift/Serie: Lecture Notes in Computer Science (Image Analysis, 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings))
• Volym: 9127
• Länkar: http://link.springer.com/chapter/10.1007%2F978-3-319-19665-7_23; http://dx.doi.org/10.1007/978-3-319-19665-7_23
• Dokumenttyp: Konferensbidrag
• Förlag: Springer
• Ämne: Computational Mathematics
• Nyckelord: Image enhancement; Discretization; Wasserstein metric
• Conference name: 19th Scandinavian Conference on Image Analysis (SCIA 2015)
• Conference date: 2015-06-15 - 2015-06-17
• Conference place: Copenhagen, Denmark
• Status: Published
• Forskningsgrupp: Mathematical Imaging Group
• ISBN/ISSN/Övrigt: ISSN: 1611-3349; ISSN: 0302-9743; ISBN: 978-3-319-19665-7; ISBN: 978-3-319-19664-0