In our image registration and processing work, we focus on thermal and visual (RGB) image registration and propose different methods to improve the quality of interspectral registration for the purpose of real-time monitoring and mobile mapping. Images captured by low-altitude UAVs represent a very challenging scenario for interspectral registration due to the strong variations in overlap, scale, rotation, point of view and structure of such scenes. Furthermore, these small-scale UAVs have limited processing and communication power. We introduce a feature descriptor (RFAE) for robustly identifying corresponding regions of images in different spectrum. We evaluated our method using a test data set consisting of 84 image pairs. In all instances our approach combined with SIFT or SURF feature-based registration was superior to the standard versions. Although we focus mainly on aerial imagery, our evaluation shows that the presented approach would also be beneficial in other scenarios such as surveillance and human detection.
The datasets can be downloaded from the links below:
Please cite the following publication if you use the datasets:
Saeed Yahyanejad and Bernhard Rinner. A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs. ISPRS Journal of Photogrammetry and Remote Sensing, 2015.