Direct linear and refraction-invariant pose estimation and calibration model for underwater imaging

Abstract

Accuracy, detail, and limited time on site make photogrammetry a valuable means for underwater mapping. Imaging in such domains is subjected however to distortions which are caused by refraction of the incoming rays. As the literature shows, these distortions are depth-dependent, non-linear, and alter the standard single viewpoint geometry. To handle their effect, we derive in this paper a refraction-invariant representation and show that despite the pronounced distortions, such a model is attainable. We also show that its contribution is not only theoretical, as it also allows to estimate the pose parameters linearly and at a significantly improved accuracy. The paper then extends the model to calibrate the underwater-related system parameters and, again, demonstrates the ability to yield a linear model, to simplify the settings and requirements for calibration procedures, and most importantly to improve the accuracy of the system parameters by an order of magnitude or more. Experiments also show enhanced accuracy and stability of the model in the presence of high-level of noise. Thus, the paper provides an in-depth look into the geometrical modeling of underwater images and at the same time offers practical enhancement of the accuracies and requirements to reach them.