# Hyperspectral 3D Mapping of Underwater Environments

arXiv: https://arxiv.org/abs/2110.06571 · HTML: https://mlsanity.com/paper/2110.06571/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 37 references that are in the map.
- First posted on arXiv 13 Oct 2021.

## Builds on (most cited first, 5 of 5)

- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization](https://mlsanity.com/paper/1910.14532/) (2019)
- [OV2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications](https://mlsanity.com/paper/2102.04060/) (2021)
- [Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments](https://mlsanity.com/paper/1806.05842/) (2018)
- [Automatic Scale Estimation of Structure from Motion based 3D Models using Laser Scalers](https://mlsanity.com/paper/1906.08019/) (2019)

## Built on by (most cited first, 1 of 1)

- [Spectral 3D Computer Vision -- A Review](https://mlsanity.com/paper/2302.08054/) (2023)

## Abstract (arXiv)

Hyperspectral imaging has been increasingly used for underwater survey applications over the past years. As many hyperspectral cameras work as push-broom scanners, their use is usually limited to the creation of photo-mosaics based on a flat surface approximation and by interpolating the camera pose from dead-reckoning navigation. Yet, because of drift in the navigation and the mostly wrong flat surface assumption, the quality of the obtained photo-mosaics is often too low to support adequate analysis.In this paper we present an initial method for creating hyperspectral 3D reconstructions of underwater environments. By fusing the data gathered by a classical RGB camera, an inertial navigation system and a hyperspectral push-broom camera, we show that the proposed method creates highly accurate 3D reconstructions with hyperspectral textures. We propose to combine techniques from simultaneous localization and mapping, structure-from-motion and 3D reconstruction and advantageously use them to create 3D models with hyperspectral texture, allowing us to overcome the flat surface assumption and the classical limitation of dead-reckoning navigation.