Skip to Main content Skip to Navigation
Journal articles

Variational Osmosis for Non-linear Image Fusion

Abstract : We propose a new variational model for nonlinear image fusion. Our approach incorporates the osmosis model proposed in Vogel et al. (2013) and Weickert et al. (2013) as an energy term in a variational model. The osmosis energy is known to realize visually plausible image data fusion. As a consequence, our method is 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. We develop a primal-dual algorithm for solving this new image fusion model and we apply the resulting minimisation scheme to multi-modal image fusion for face fusion, colour transfer and some cultural heritage conservation challenges. Visual comparison to state-of-the-art proves the quality and flexibility of our method.
Document type :
Journal articles
Complete list of metadatas


https://hal.archives-ouvertes.fr/hal-02314972
Contributor : Nicolas Papadakis <>
Submitted on : Monday, October 21, 2019 - 3:26:03 PM
Last modification on : Thursday, October 29, 2020 - 2:02:01 PM

Annex

Identifiers

  • HAL Id : hal-02314972, version 1
  • ARXIV : 1910.02012

Collections

Citation

Simone Parisotto, Luca Calatroni, Aurélie Bugeau, Nicolas Papadakis, Carola-Bibiane Schönlieb. Variational Osmosis for Non-linear Image Fusion. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2020, 29, pp.5507-5516. ⟨hal-02314972⟩

Share

Metrics

Record views

161

Files downloads

16