DLR HySU (HyperSpectral Unmixing) dataset

The DLR HySU (HyperSpectral Unmixing) dataset provides a publicly available benchmark to assess the performance of spectral unmixing algorithms. The dataset consists of airborne data acquired by a HySpex imaging spectrometer and a 3K RGB camera system over DLR premises at Oberpfaffenhofen, complemented by in-situ spectra recorded with an SVC field spectrometer. Synthetic targets of five different materials (bitumen, red metal, blue fabric, red fabric and green fabric) and sizes (0.25, 0.5, 1, 2 and 3 m) are deployed over a homogeneous background within the survey area in order to simulate various mixing scenarios. For a straightforward validation of unmixing algorithms, spectral libraries of the five target materials and the areas of all targets are also provided. The DLR HySU benchmark dataset is especially designed to test the main steps of spectral unmixing, namely dimensionality estimation, endmember extraction with and without pure pixel assumption, and abundance estimation. Other applications that can be investigated with DLR HySU include target detection, denoising, and super-resolution methods.