Anomaly detection and target recognition with hyperspectral images

In this study, a new method that can perform anomaly detection and target recognition gradually with hyperspectral images (HSI) is introduced. This study constitutes the lower step a system that can process the HSI obtained by unmanned aerial vehicle (UAV) quickly and can enable the anomaly detection and target recognition process done in the mission time of UAV. In the proposed model, firstly the unusual pixels in the HSI data are detected, and then it is investigated whether these pixels are belonging to a target defined. These two phases in the model are carried out using artificial neural network that is a technique of the artificial intelligence. In the model, Parallel programming methods that run with CUDA platform on the GPU are proposed for the processing power requirement resulting from size of HSI.