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Authors: Feras Almasri and Olivier Debeir

Affiliation: LISA - Laboratory of Image Synthesis and Analysis, Université Libre de Bruxelles CPI 165/57, Avenue Franklin Roosevelt 50, 1050 Brussels, Belgium

Keyword(s): Colorization, Deep learning, Thermal images, Nigh Vision.

Abstract: Transforming a thermal infrared image into a robust perceptual colour visual image is an ill-posed problem due to the differences in their spectral domains and in the objects’ representations. Objects appear in one spectrum but not necessarily in the other, and the thermal signature of a single object may have different colours in its visual representation. This makes a direct mapping from thermal to visual images impossible and necessitates a solution that preserves texture captured in the thermal spectrum while predicting the possible colour for certain objects. In this work, a deep learning method to map the thermal signature from the thermal image’s spectrum to a visual representation in their low-frequency space is proposed. A pan-sharpening method is then used to merge the predicted low-frequency representation with the high-frequency representation extracted from the thermal image. The proposed model generates colour values consistent with the visual ground truth when the obje ct does not vary much in its appearance and generates averaged grey values in other cases. The proposed method shows robust perceptual night vision images in preserving the object’s appearance and image context compared with the existing state-of-the-art. (More)

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Paper citation in several formats:
Almasri, F. and Debeir, O. (2020). Robust Perceptual Night Vision in Thermal Colorization. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 348-356. DOI: 10.5220/0008979603480356

@conference{visapp20,
author={Feras Almasri. and Olivier Debeir.},
title={Robust Perceptual Night Vision in Thermal Colorization},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={348-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008979603480356},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Robust Perceptual Night Vision in Thermal Colorization
SN - 978-989-758-402-2
IS - 2184-4321
AU - Almasri, F.
AU - Debeir, O.
PY - 2020
SP - 348
EP - 356
DO - 10.5220/0008979603480356
PB - SciTePress

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