论文标题
WHU-HI：具有高空间分辨率（H2）基准数据集用于高光谱图像分类
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets for hyperspectral image classification
论文作者
论文摘要
分类是高光谱图像处理和应用的重要方面。目前，研究人员主要将经典的机载高光谱图像用作基准数据集。但是，现有的数据集遭受三个瓶颈的影响：（1）低空间分辨率； （2）低标记的像素比例； （3）较低程度的子类区别。在本文中，一个新的基准数据集名为Wuhan无人机高光谱图像（WHU-HI）数据集用于高光谱图像分类。具有高光谱分辨率（NM级）和非常高的空间分辨率（CM级）的WHU-HI数据集，我们在此称为H2成像器。此外，WHU-HI数据集具有较高的像素标签率和较细的子类。一些高光谱图像分类方法基准了WHU-HI数据集，实验结果表明WHU-HI是一个具有挑战性的数据集。我们希望WHU-HI数据集可以成为加速未来研究的强大基准。
Classification is an important aspect of hyperspectral images processing and application. At present, the researchers mostly use the classic airborne hyperspectral imagery as the benchmark dataset. However, existing datasets suffer from three bottlenecks: (1) low spatial resolution; (2) low labeled pixels proportion; (3) low degree of subclasses distinction. In this paper, a new benchmark dataset named the Wuhan UAV-borne hyperspectral image (WHU-Hi) dataset was built for hyperspectral image classification. The WHU-Hi dataset with a high spectral resolution (nm level) and a very high spatial resolution (cm level), which we refer to here as H2 imager. Besides, the WHU-Hi dataset has a higher pixel labeling ratio and finer subclasses. Some start-of-art hyperspectral image classification methods benchmarked the WHU-Hi dataset, and the experimental results show that WHU-Hi is a challenging dataset. We hope WHU-Hi dataset can become a strong benchmark to accelerate future research.
