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arXiv · 1604.02245

Infrared Colorization Using Deep Convolutional Neural Networks

Matthias Limmer·Hendrik P. A. Lensch
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Abstract

This paper proposes a method for transferring the RGB color spectrum to near-infrared (NIR) images using deep multi-scale convolutional neural networks. A direct and integrated transfer between NIR and RGB pixels is trained. The trained model does not require any user guidance or a reference image database in the recall phase to produce images with a natural appearance. To preserve the rich details of the NIR image, its high frequency features are transferred to the estimated RGB image. The presented approach is trained and evaluated on a real-world dataset containing a large amount of road scene images in summer. The dataset was captured by a multi-CCD NIR/RGB camera, which ensures a perfect pixel to pixel registration.

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Matthias Limmer, Hendrik P. A. Lensch. 2016-04-08. Infrared Colorization Using Deep Convolutional Neural Networks. https://arxiv.org/abs/1604.02245

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