A Trillion Coral Reef Colors: Deeply Annotated Underwater Hyperspectral Images for Automated Classification and Habitat Mapping
A Trillion Coral Reef Colors: Deeply Annotated Underwater Hyperspectral Images for Automated Classification and Habitat Mapping
复制标题
万亿珊瑚礁颜色：深度注释的水下高光谱图像，用于自动分类和栖息地测绘
作者：
Ahmad Rafiuddin Rashid;A. Chennu
本文描述了一个大型水下高光谱图像数据集，可供计算机视觉、机器学习、遥感和珊瑚礁生态学领域的研究人员使用。我们介绍了水下数据采集、处理和管理的详细信息，以创建这个大型珊瑚礁图像数据集，并注释用于栖息地测绘。使用潜水员操作的高光谱成像系统 (HyperDiver) 对加勒比库拉索岛周围 8 个珊瑚礁地点的 147 个样线进行了调查。水下近端传感方法生成了精细尺度的海底图像，其中包含超过 22 亿个详细光谱点。其中，超过 1000 万个数据点已被注释为栖息地描述符或分类学身份，共有 47 个类标签，直至属和种级别。除了 HyperDiver 调查数据之外，我们还包括沿 147 个横断面中的 23 个进行的传统（彩色照片）样方调查的图像和注释，这使得两种类型的珊瑚礁调查方法之间的珊瑚礁描述能够进行比较。该数据集有望为分类算法、高光谱图像分割和自动栖息地测绘带来好处。
This paper describes a large dataset of underwater hyperspectral imagery that can be used by researchers in the domains of computer vision, machine learning, remote sensing, and coral reef ecology. We present the details of underwater data acquisition, processing and curation to create this large dataset of coral reef imagery annotated for habitat mapping. A diver-operated hyperspectral imaging system (HyperDiver) was used to survey 147 transects at 8 coral reef sites around the Caribbean island of Curaçao. The underwater proximal sensing approach produced fine-scale images of the seafloor, with more than 2.2 billion points of detailed optical spectra. Of these, more than 10 million data points have been annotated for habitat descriptors or taxonomic identity with a total of 47 class labels up to genus- and species-levels. In addition to HyperDiver survey data, we also include images and annotations from traditional (color photo) quadrat surveys conducted along 23 of the 147 transects, which enables comparative reef description between two types of reef survey methods. This dataset promises benefits for efforts in classification algorithms, hyperspectral image segmentation and automated habitat mapping.