  Recently, a new underwater imaging formation model presented that the
coefficients related to the direct and backscatter transmission signals are
dependent on the type of water, camera specifications, water depth, and imaging
range. This paper proposes an underwater color correction method that
integrates this new model on an underwater robot, using information from a
pressure depth sensor for water depth and a visual odometry system for
estimating scene distance. Experiments were performed with and without a color
chart over coral reefs and a shipwreck in the Caribbean. We demonstrate the
performance of our proposed method by comparing it with other statistic-,
physic-, and learning-based color correction methods. Applications for our
proposed method include improved 3D reconstruction and more robust underwater
robot navigation.
