Deep Sea Robotic Imaging Simulator

TL;DR

This paper introduces a physics-based simulation model for generating realistic deep sea underwater images to aid research, addressing the scarcity of real deep sea data and enabling improved training and evaluation of underwater vision systems.

Contribution

It presents a novel radiometric image formation model considering attenuation, scattering, and artificial illumination, with an efficient rendering strategy for deep sea image simulation.

Findings

Effective simulation of deep sea images with realistic lighting effects

Integration into UUV simulator for practical testing

Public release of the image converter source code

Abstract

Nowadays underwater vision systems are being widely applied in ocean research. However, the largest portion of the ocean - the deep sea - still remains mostly unexplored. Only relatively few image sets have been taken from the deep sea due to the physical limitations caused by technical challenges and enormous costs. Deep sea images are very different from the images taken in shallow waters and this area did not get much attention from the community. The shortage of deep sea images and the corresponding ground truth data for evaluation and training is becoming a bottleneck for the development of underwater computer vision methods. Thus, this paper presents a physical model-based image simulation solution, which uses an in-air texture and depth information as inputs, to generate underwater image sequences taken by robots in deep ocean scenarios. Different from shallow water conditions, artificial illumination plays a vital role in deep sea image formation as it strongly affects the scene appearance. Our radiometric image formation model considers both attenuation and scattering effects with co-moving spotlights in the dark. By detailed analysis and evaluation of the underwater image formation model, we propose a 3D lookup table structure in combination with a novel rendering strategy to improve simulation performance. This enables us to integrate an interactive deep sea robotic vision simulation in the Unmanned Underwater Vehicles simulator. To inspire further deep sea vision research by the community, we will release the source code of our deep sea image converter to the public.