Journal of Robotics, Networking and Artificial Life
Online ISSN : 2352-6386
Print ISSN : 2405-9021
Underwater Image Restoration Using In-situ Turbidity Measurements
Irmiya R. Inniyaka Yuya NishidaKazuo Ishii
著者情報
ジャーナル オープンアクセス

2023 年 10 巻 2 号 p. 141-151

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Degradation in underwater imaging is as a result of absorption and scattering of light. Propagated visible light rays through the water column are absorbed at rates that vary depending on the wavelength of light. Large suspended particles also scatter the propagated light rays, as can be observed in an underwater environment. Furthermore, color is distorted due to the inverse ratio of attenuation that is proportional to the wavelength of light through a unit of length through the water column. These phenomena distort underwater images by making them appear dark and have low contrast. Conventional underwater image restoration techniques are largely based on the image formation model (IMF) which restores the image based on estimates from the degraded images. The results are solutions that are limited to specific underwater conditions. In this paper, we propose a novel restoration strategy by considering the optical properties in the underwater environment at the time of image capture, a robust restoration technique can be applied to images captured in different underwater conditions. In so doing, we design a turbidity meter that capture wavelength-dependent absorption data which are applied as parameters to restore the distorted images based on the RGB channels. To validate our proposed technique, we conduct experiments in a controlled underwater environment while varying the concentration of suspended particles based on degree of kaolin mixture.

著者関連情報
© 2023 ALife Robotics Corporation Ltd.

この記事はクリエイティブ・コモンズ [表示 - 非営利 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc/4.0/deed.ja
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