Jens T. Thielemann

In this work, we have investigated the properties of light transport in turbid water for underwater 3D imaging, by comparing literature, simulations, and experiments. The work is motivated by a need for high-quality 3D image data for underwater robotics, also in turbid waters. We present a comparative analysis of how sine wave and line patterns degrade upon propagation through turbid water, and explain the difference in degradation through analysis of the signal response of the water. We find that line patterns provide a sharp signal peak from the un-scattered (ballistic) photons, with a very broad skirt of scattered signal. The detection of the un-scattered peak allows for sub-millimeter 3D reconstruction quality at water turbidities up to 4.8 NTU (nephelometric turbidity units). Using sine waves, 3D precision rapidly drops, as the scattered signal from large parts of the scene causes rapid loss of signal contrast. 3D reconstruction fails at turbidities above 3.1 NTU. In dark parts of the scene, both signal types yield incorrect 3D reconstruction, as forward scattered signal from surrounding brighter regions dominate over the correct signal peak. In line with literature on scattering properties of water, we find that the use of long wavelengths (red signal) gives less scattering and higher signal contrast compared with the use of green and blue, thereby providing lower 3D noise.

Aquaculture net cage inspection and maintenance is a central issue in fish farming. Inspection using autonomous underwater vehicles is a promising solution. This paper proposes laser-camera triangulation for pose estimation to enable autonomous net following for an autonomous vehicle. The laser triangulation 3D data is experimentally compared to a doppler velocity log (DVL) in an active fish farm. We show that our system is comparable in performance to a DVL for distance and angular pose measurements. Laser triangulation is promising as a short distance ranging sensor for autonomous vehicles at a low cost compared to acoustic sensors.

High-precision underwater 3D cameras are required to automate many of the traditional subsea inspection, maintenance and repair (IMR) operations. In this paper we introduce a novel multi-frequency phase stepping (structured light) method for high-precision 3D estimation even in turbid water. We introduce an adaptive phase-unwrapping procedure which uses the phase-uncertainty to determine the highest frequency that can be reliably unwrapped. Light scattering adversely affects the phase estimate. We propose to remove the effect of forward scatter with an unsharp filter and a model-based method to remove the backscatter effect. Tests in varying turbidity show that the scatter correction removes the adverse effect of scatter on the phase estimates. The adaptive frequency unwrapping with scatter correction results in images with higher accuracy and precision and less phase unwrap errors than the Gray-Code Phase Stepping (GCPS) approach.

High-quality video observations are very much needed in underwater environments for the monitoring of several ecosystem indicators and to support the sustainable development and management of almost all activities in the ocean. Reliable video observations are however challenging to collect, because of the generally poor visibility conditions and the difficulties to deploy cost-effective sensors and platforms in the marine environment. Visibility in water is regulated by natural light availability at different depths, and by the presence of suspended particles, scattering incident light in all directions. Those elements are also largely variable in time and space, making it difficult to identify technological solutions that can be used in all conditions. By combining state-of-the-art “time of flight” (ToF) image sensors and innovative pulsed laser illumination, we have developed a range-gated camera system (UTOFIA) that enables affordable and enhanced 3D underwater imaging at high resolution. This range-gated solution allows users to eliminate close-range backscattering, improving quality of the images and providing information on the distance of each illuminated object, hence giving access to real-time 3D measurements. Furthermore, as the system is based on pulsed laser light, it is almost independent of natural light conditions and can achieve similar performances at an extended depth range. We use this system to collect observations in different oceanographic conditions and for different applications, including aquaculture monitoring, seafloor mapping, litter identifications and structure inspection. Performances are evaluated by comparing images to regular cameras and by using standard targets to assess accuracy and precision of distance measurements. We suggest that this type of technology can become a standard in underwater 3D imaging to support the future development of the ocean economy.

Sensors that can provide detailed 3D data underwater are a prerequisite for enabling autonomous inspection of e.g. seafloor integrity, ocean habitats and subsea installations with unmanned underwater vehicles. Sonars are currently the primary source of 3D data on moving platforms subsea but have limited depth and lateral resolution. Several optical approaches exist such as passive stereo, which have problems with textureless objects, and LIDARs which are slow and provide low lateral resolution. In this work we explore the use of structured light, to achieve high-resolution 3D of objects in an underwater environment. We have adapted a Gray Code Phase Stepping (GCPS) structured light approach to be more robust to the contrast degradation caused by the scattering and attenuation of light in water. The robustness towards increasing water turbidity has been verified in pool experiments. We achieve a depth resolution ranging from 1.4mm to 6.4mm depending on the turbidity when imaging an object at 1.1m distance with a pixel resolution of 1280x1024 at a framerate of 8Hz.

In this paper we present how to exploit a combination of an underwater range-gated imaging system and an unsharp filtering method to effectively suppress the effects of forward- and backward-scatter. Typically, back-scattered light causes a contrast reduction in the image, while forward-scattered light causes a blurring of features. A range-gated imaging system can effectively suppress the majority of back-scatter by gating close to objects of interest, however, such systems do not have an inherent way of suppressing forward-scatter. The proposed range-gated system facilitates real-time 3D because it facilitates range-gated acquisition at 1kHz with an inter-range spacing of 18.8cm. A peak finding algorithm working on the range-gated sweep signal is used to estimate 3D. However, the scattering effects also cause unwanted peaks in the range-gated signal. The effect of forward-scatter (spatial blur) for the peak finding algorithm is that the extent of objects may be larger in the reported depth map than the real physical extent of the object. This can be detrimental to e.g., biomass estimation of fish. In this paper we describe an unsharp mask filtering approach to remove the combined effect of forward and backward-scatter on each individual range-gated image before the 3D peak finding algorithm is applied. The results of the proposed filtering are twofold: 1) removing the residual back-scatter which leads to a contrast increase in the gated images, and 2) removal of false-positive peaks in the range-gated signal due to forward-scatter. This leads to more accurate depth maps.

This paper describes a 3D measurement algorithm based on Multi-Frequency Phase Stepping, using a single period pattern and a higher frequency pattern. An experimentally verified analytical expression for depth precision enables adaptive selection of the high frequency. The algorithm has several advantages compared with Gray Code Phase Stepping (GCPS): In high signal situations, depth precision improves. In low signal situations, Gray Coding errors are avoided. Additionally, robust estimates of measurement precision will be available on a per pixel basis.