Real-time Model-based Image Color Correction for Underwater Robots
This work addresses color correction for underwater robots to enhance 3D reconstruction and navigation, but it is incremental as it builds on a recent model with sensor integration.
The paper tackles the problem of underwater color correction by integrating a new imaging formation model with depth and distance sensors on an underwater robot, achieving improved performance compared to existing methods in experiments on coral reefs and shipwrecks.
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.