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Heat-assisted imaging enables day-like visibility at night

An imaging technique that uses a neural-network model to obtain physical information from infrared radiation improves on existing techniques in low-visibility situations, and could be deployed immediately in autonomous vehicles.
  1. Manish Bhattarai

    1. Manish Bhattarai is in the Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

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  2. Sophia Thompson

    1. Sophia Thompson is in the Department of Biology, University of New Mexico, Albuquerque, New Mexico 87106, USA.

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Image detection and classification techniques are indispensable for technologies such as autonomous vehicles, which are set to make an indelible mark on the twenty-first century. But these methods still face considerable challenges when visibility is low — either because of weather conditions such as fog and smoke, or as a result of something as commonplace as the natural hours of darkness. Writing in Nature, Bao et al.1 present heat-assisted detection and ranging (HADAR) technology, a groundbreaking approach that uses thermal imaging, physics and machine learning to shine light on the problem of low-visibility detection.

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Nature 619, 699-700 (2023)

doi: https://doi.org/10.1038/d41586-023-02333-x

References

  1. Bao, F. et al. Nature 619, 743–748 (2023).

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  2. Gurton, K. P., Yuffa, A. J. & Videen, G. W. Opt. Lett. 39, 3857–3859 (2014).

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  3. Marnissi, M. A. & Fathallah, A. in Proc. IEEE/CVF Conf. Computer Vision and Pattern Recognition 817–825 (IEEE, 2023).

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  4. Kwasniewska, A., Szankin, M., Ruminski, J., Sarah, A. & Gamba, D. in Proc. IEEE/CVF Conf. Computer Vision and Pattern Recognition 3852–3862 (IEEE, 2021).

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Competing Interests

The authors declare no competing interests.

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