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Variational Osmosis for Non-linear Image Fusion.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Calatroni, Luca 
Bugeau, Aurelie 
Papadakis, Nicolas 
Schonlieb, Carola-Bibiane 

Abstract

We propose a new variational model for non-linear image fusion. Our approach is based on the use of an osmosis energy term related to the one studied in Vogel et al. [44] and Weickert et al. [45]. The minimization of the proposed non-convex energy realizes visually plausible image data fusion, invariant to multiplicative brightness changes. On the practical side, it requires minimal supervision and parameter tuning and can encode prior information on the structure of the images to be fused. For the numerical solution of the proposed model, we develop a primal-dual algorithm and we apply the resulting minimization scheme to solve multi-modal face fusion, color transfer and cultural heritage conservation problems. Visual and quantitative comparisons to state-of-the-art approaches prove the out-performance and the flexibility of our method.

Description

Keywords

Osmosis filtering, image fusion, non-convex optimization, primal-dual algorithm, cultural heritage imaging

Journal Title

IEEE Trans Image Process

Conference Name

Journal ISSN

1057-7149
1941-0042

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Rights

All rights reserved
Sponsorship
Engineering and Physical Sciences Research Council (EP/M00483X/1)
Engineering and Physical Sciences Research Council (EP/N014588/1)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (691070)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (777826)
Leverhulme Trust (RPG-2018-121)
Leverhulme Trust (PLP-2017-275)
Alan Turing Institute (Unknown)
EPSRC (EP/S026045/1)