Presentation + Paper
22 April 2020 Adaptation of Koschmieder dehazing model for underwater marker detection
Jaouad Hajjami, Thibault Napoléon, Ayman Alfalou
Author Affiliations +
Abstract
Most of dehazing algorithms are based on the well known Koschmieder image restoration model working on color images. Nowadays, many autonomous underwater vehicles use marker detection in order to estimate their 3D pose according to the marked target. In this paper, we propose an adaptation of the Koschmieder for grayscale images which is more suitable for marker detection. This is done by enhancing the final energy (the radiance) of the image lost during the processing. We show that by multiplying the final radiance image by the shifted transmission of the Koschmieder model, we can enhance the gradient and the contrast of the image. We have implemented our Koschmieder adaptation into two methods from the literature and proven its robustness on an underwater dataset containing ArUco markers. The obtained results outperform the existing methods in terms of marker detection rate without degrading the pose estimation.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jaouad Hajjami, Thibault Napoléon, and Ayman Alfalou "Adaptation of Koschmieder dehazing model for underwater marker detection", Proc. SPIE 11400, Pattern Recognition and Tracking XXXI, 1140003 (22 April 2020); https://doi.org/10.1117/12.2559051
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KEYWORDS
Air contamination

Image enhancement

Image transmission

Visual process modeling

Visualization

Image restoration

Cameras

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