Combining strong features for registration of hyperspectral and lidar data from field-based platforms

This paper presents an approach to automatically register hyperspectral images with lidar point clouds using a combination of SIFT and SURF feature descriptors. The aim is to generate 3D terrain maps of the environment combining spectral and geometrical information. The datasets are acquired from field-based platforms which, due to the lack of georeferencing, cannot be simply fused and require a registration processing step. In addition, some applications, such as in mining, cannot rely on reliable GPS signal. The proposed method is validated using experimental data acquired from vertical mine walls.