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

arXiv: https://arxiv.org/abs/1904.06437 · HTML: https://mlsanity.com/paper/1904.06437/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2019.

## Built on by (most cited first, 4 of 4)

- [Real-Time Dense 3D Mapping of Underwater Environments](https://mlsanity.com/paper/2304.02704/) (2023)
- [High Definition, Inexpensive, Underwater Mapping](https://mlsanity.com/paper/2203.05640/) (2022)
- [SM/VIO: Robust Underwater State Estimation Switching Between Model-based and Visual Inertial Odometry](https://mlsanity.com/paper/2304.01988/) (2023)
- [Improving the perception of visual fiducial markers in the field using Adaptive Active Exposure Control](https://mlsanity.com/paper/2404.12055/) (2024)

## Abstract (arXiv)

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.