Multisensor image fusion based on generative adversarial networks

M. A. Lebedev; D. V. Komarov; O. V. Vygolov; Yu. V. Vizilter

doi:10.1117/12.2533098

7 October 2019 Multisensor image fusion based on generative adversarial networks

M. A. Lebedev, D. V. Komarov, O. V. Vygolov, Yu. V. Vizilter

Proceedings Volume 11155, Image and Signal Processing for Remote Sensing XXV; 111551T (2019) https://doi.org/10.1117/12.2533098
Event: SPIE Remote Sensing, 2019, Strasbourg, France

Abstract

The paper addresses the further advance in our complex research in the field of multisensory image fusion based on generative adversarial models [1-2] and their application to such practical tasks as visual representation of fused images, acquired in different spectral ranges (e.g. TV and IR), and changes detection on images, acquired in different conditions (e.g. season-varying images). A developed architecture of a neural network based on pix2pix model is presented, which can solve the both tasks mentioned above. A technique for generating training and test datasets including data augmentation process is described. The results are demonstrated on real-world images.

Citation Download Citation

M. A. Lebedev, D. V. Komarov, O. V. Vygolov, and Yu. V. Vizilter "Multisensor image fusion based on generative adversarial networks", Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111551T (7 October 2019); https://doi.org/10.1117/12.2533098

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KEYWORDS

Image fusion

Network architectures

Infrared imaging

Infrared radiation

Visible radiation

Image processing

Neural networks

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