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The use of underwater hyperspectral imaging deployed on remotely operated vehicles - methods and applications

机译:部署在遥控车辆上的水下高光谱成像的使用-方法和应用

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Abstract: Currently a new underwater hyperspectral imager (UHI) have been deployed on Remotely Operated Vehicles (ROV) for a more automated identification, mapping and monitoring of bio-geo-chemical objects of interest (OOI). Sea floor maps based on UHI can be used to classify 001 based on specific optical fingerprints providing spectral upwelling radiance or reflectance with up to 1 nm spectral resolution in the visible range for each image pixel. Different habitats comprising soft bottom, deep and cold water coral reefs, sponge habitats, pipeline monitoring and kelp forest maps are examples for UHI-based mapping. Characterising material surface on man-made objects such as corrosion on pipelines and subsea structures and archaeological objects are other examples. The overall image quality and identification success of OOI can be optimized if movements of the ROV is controlled by a dynamic position (DP) system and corresponding speed, altitude, pitch, roll and yaw control. Likewise, illumination control is important to provide proper light intensity, spectral composition and illumination evenness of OOI to enhance data quality. The benefits of using UHI for seafloor habitat mapping can be evaluated by four categories of resolution. These are A) spatial resolution (image pixel size), B) spectral resolution (1-10 nm, 400-800 nm), C) radiometric resolution (dynamic range, bits per pixel), and D) temporal resolution for time-series and monitoring. These categories of resolution are discussed with respect to OOI identification and mapping using different case examples.
机译:摘要:目前,一种新型的水下高光谱成像仪(UHI)已部署在远程操作车辆(ROV)上,以实现对感兴趣的生物地球化学物体(OOI)的更自动识别,制图和监视。基于UHI的海底图可用于基于特定的光学指纹对001进行分类,这些光学指纹在每个图像像素的可见范围内提供高达1 nm的光谱分辨率的光谱上升辐射或反射率。基于UHI的地图绘制的示例包括软底,深水和冷水珊瑚礁,海绵栖息地,管道监控和海带森林地图等不同的栖息地。其他实例包括在人造物体上表征材料表面,例如管道和海底结构上的腐蚀以及考古物体。如果ROV的运动由动态位置(DP)系统以及相应的速度,高度,俯仰,横滚和偏航控制来控制,则可以优化OOI的总体图像质量和识别成功率。同样,照明控制对于提供适当的OOI光强度,光谱组成和照明均匀度以提高数据质量也很重要。将UHI用于海底栖息地制图的好处可以通过四种分辨率来评估。这些是A)空间分辨率(图像像素大小),B)光谱分辨率(1-10 nm,400-800 nm),C)辐射分辨率(动态范围,每像素位数)和D)时间序列的时间分辨率和监控。使用不同的案例,针对OOI标识和映射讨论了这些分辨率类别。

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