Regularizing Image Intensity Transformations Using the Wasserstein Metric
(2015) 19th Scandinavian Conference on Image Analysis (SCIA 2015) 9127. p.275-286- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8052142
- author
- Oskarsson, Magnus LU
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Image enhancement, Discretization, Wasserstein metric
- host publication
- Lecture Notes in Computer Science (Image Analysis, 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings))
- editor
- Paulsen, Rasmus and Pedersen, Kim
- volume
- 9127
- pages
- 12 pages
- publisher
- Springer
- conference name
- 19th Scandinavian Conference on Image Analysis (SCIA 2015)
- conference location
- Copenhagen, Denmark
- conference dates
- 2015-06-15 - 2015-06-17
- external identifiers
-
- scopus:84947938680
- ISSN
- 1611-3349
- 0302-9743
- ISBN
- 978-3-319-19665-7
- 978-3-319-19664-0
- DOI
- 10.1007/978-3-319-19665-7_23
- language
- English
- LU publication?
- yes
- id
- 71057566-a401-4d40-b9b6-b0ed14beeb17 (old id 8052142)
- alternative location
- http://link.springer.com/chapter/10.1007%2F978-3-319-19665-7_23
- date added to LUP
- 2016-04-01 10:07:42
- date last changed
- 2024-10-06 20:57:25
@inproceedings{71057566-a401-4d40-b9b6-b0ed14beeb17, abstract = {{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.}}, author = {{Oskarsson, Magnus}}, booktitle = {{Lecture Notes in Computer Science (Image Analysis, 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark, June 15-17, 2015. Proceedings))}}, editor = {{Paulsen, Rasmus and Pedersen, Kim}}, isbn = {{978-3-319-19665-7}}, issn = {{1611-3349}}, keywords = {{Image enhancement; Discretization; Wasserstein metric}}, language = {{eng}}, pages = {{275--286}}, publisher = {{Springer}}, title = {{Regularizing Image Intensity Transformations Using the Wasserstein Metric}}, url = {{http://dx.doi.org/10.1007/978-3-319-19665-7_23}}, doi = {{10.1007/978-3-319-19665-7_23}}, volume = {{9127}}, year = {{2015}}, }