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.
翻译:过去几年来,在水下勘测应用中越来越多地使用了超光谱成像。许多超光谱照相机作为推入式扫描仪,其使用通常限于在平面近近近和通过将镜头从死亡反射导航中成形的中间图解来创建光-摩西照相机。然而,由于导航中的漂浮和大部分错误的平面假设,获得的光-摩西摄影机的质量往往太低,无法进行充分分析。在本文中,我们介绍了创建水下环境超光谱3D重建的初步方法。通过利用经典RGB照相机、惯性导航系统和超光谱推入式照相机收集的数据,我们展示了拟议方法以超光谱光谱纹理制作高度精确的3D重建技术。我们提议将同时进行本地化和绘图、结构自感动和3D重建的技术结合起来,并有利地利用这些技术创建高光谱纹3D模型,使我们能够克服平坦地表假设和对死亡反射导航的典型限制。