PeRL STUDIES AUTONOMOUS NAVIGATION & MAPPING FOR MOBILE ROBOTS IN A PRIORI UNKNOWN ENVIRONMENTS.

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Initial results in underwater single image dehazing

Summary


Nicholas Carlevaris-Bianco, Anush Mohan and Ryan M. Eustice, Initial results in underwater single image dehazing. In Proceedings of the IEEE/MTS OCEANS Conference and Exhibition, pages 1-8, Seattle, WA, USA, September 2010.

Abstract

As light is transmitted from subject to observer it is absorbed and scattered by the medium it passes through. In mediums with large suspended particles, such as fog or turbid water, the effect of scattering can drastically decrease the quality of images. In this paper we present an algorithm for removing the effects of light scattering, referred to as dehazing, in underwater images. Our key contribution is to propose a simple, yet effective, prior that exploits the strong difference in attenuation between the three image color channels in water to estimate the depth of the scene. We then use this estimate to reduce the spatially varying effect of haze in the image. Our method works with a single image and does not require any specialized hardware or prior knowledge of the scene. As a by-product of the dehazing process, an up-to-scale depth map of the scene is produced. We present results over multiple real underwater images and over a controlled test set where the target distance and true colors are known.

Bibtex entry

@INPROCEEDINGS { ncarlevaris-2010a,
    AUTHOR = { Nicholas Carlevaris-Bianco and Anush Mohan and Ryan M. Eustice },
    TITLE = { Initial results in underwater single image dehazing },
    BOOKTITLE = { Proceedings of the IEEE/MTS OCEANS Conference and Exhibition },
    YEAR = { 2010 },
    MONTH = { September },
    ADDRESS = { Seattle, WA, USA },
    PAGES = { 1--8 },
}