Abstract

In underwater computer vision, images are influenced by the water in two different ways. First, while still traveling through the water, light is absorbed and scattered, both of which are wavelength dependent, thus create the typical green or blue hue in underwater images. Secondly, when entering the underwater housing, the rays are refracted, affecting image formation geometrically. When using underwater images in for ex- ample Structure-from-Motion applications, both effects need to be taken into account. Therefore, we present a novel method for calibrating the parameters of an underwater camera housing. An evolutionary optimiza- tion algorithm is coupled with an analysis-by-synthesis approach, which allows to calibrate the parameters of a light propagation model for the local water body. This leads to a highly accurate calibration method for camera-glass distance and glass normal with respect to the optical axis. In addition, a model for the distance dependent effect of water on light propagation is parametrized and can be used for color correction.