Spectral Absorption from Two-view Hyperspectral Images

Kenta Kageyama, Ryo Kawahara, Takahiro Okabe

2022

Abstract

When light passes through a liquid, its energy is attenuated due to absorption. The attenuation depends both on the spectral absorption coefficient of a liquid and on the optical path length of light, and is described by the Lambert-Beer law. The spectral absorption coefficients of liquids are often unknown in real-world applications and to be measured/estimated in advance, because they depend not only on liquid media themselves but also on dissolved materials. In this paper, we propose a method for estimating the spectral absorption coefficient of a liquid only from two-view hyperspectral images of an under-liquid scene taken from the outside of the liquid in a passive and non-contact manner. Specifically, we show that the estimation results in Non-negative Matrix Factorization (NMF) because both the objective variables and the explanatory variables are all nonnegative, and then study the ambiguity in matrix factorization. We conducted a number of experiments using real hyperspectral images, and confirmed that our method works well and is useful for reconstructing shape of an under-liquid scene.

Paper Citation

in Harvard Style

Kageyama K., Kawahara R. and Okabe T. (2022). Spectral Absorption from Two-view Hyperspectral Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 715-721. DOI: 10.5220/0010917600003124

in Bibtex Style

@conference{visapp22,
author={Kenta Kageyama and Ryo Kawahara and Takahiro Okabe},
title={Spectral Absorption from Two-view Hyperspectral Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={715-721},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010917600003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Spectral Absorption from Two-view Hyperspectral Images
SN - 978-989-758-555-5
AU - Kageyama K.
AU - Kawahara R.
AU - Okabe T.
PY - 2022
SP - 715
EP - 721
DO - 10.5220/0010917600003124
PB - SciTePress