Hyperspectral 3D Mapping of Underwater Environments

TL;DR

This paper introduces a novel method for creating accurate 3D hyperspectral reconstructions of underwater environments by integrating data from RGB cameras, inertial navigation, and hyperspectral sensors, overcoming previous limitations.

Contribution

It presents an initial approach that fuses multiple sensor data to produce detailed 3D models with hyperspectral textures, surpassing flat surface and dead-reckoning constraints.

Findings

High-accuracy 3D hyperspectral reconstructions achieved

Overcomes flat surface and dead-reckoning limitations

Integrates multiple sensors for improved underwater mapping

Abstract

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.