Adaptation of Koschmieder dehazing model for underwater marker detection

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.