Hyperspectral image dataset of unstructured terrains for UGV perception

 Terrain perception for unmanned ground vehicles (UGVs) is one of the challenging tasks in machine vision. Especially when it comes to scene understanding, RGB images carry considerably less information than hyperspectral or multispectral images. Therefore, our approach was to use hyperspectral imaging methods for terrain perception. Even though hyperspectral images contain hundreds of image bands, it can be used to generate multispectral images by band selection using various band selection algorithms. This dataset is a combination of hyperspectral and multispectral images for UGV terrain perception in unstructured terrain (offroad) scenarios. Multispectral images are generated from the original hyperspectral images acquired using Specim IQ mobile hyperspectral camera which offers 400 – 1000 nm spectral range with 204 image bands. With spectral resolution of 7nm, the camera provides 512 x 512 pixels spatial resolution for hyperspectral images while 1280 x 960 pixels spatial resolution of RGB images.  The unstructured terrain image data collected in Estonia in the neighbourhood of Tallinn. All the images were captured during daylight hours. Total number of images in the dataset is 137 images including 204 band images of hyperspectral and 9, 16, 25 bands multispectral images. The wavelength details can be found in the accompanying thesis titled “Smart Terrain Perception Using Hyperspectral Imaging”.