# Real-time Model-based Image Color Correction for Underwater Robots

## TL;DR

This paper introduces a real-time, model-based underwater image color correction method for robots, utilizing water depth and scene distance data to improve visual accuracy in complex underwater environments.

## Contribution

It integrates a new underwater imaging model with robot sensors for real-time color correction, enhancing underwater robot navigation and 3D reconstruction.

## Key findings

- Outperforms existing color correction methods in experiments
- Improves underwater robot navigation robustness
- Enhances 3D reconstruction accuracy underwater

## Abstract

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.