Reduction of false alarms caused by background boundaries in real time subspace RX anomaly detection

Hyperspectral anomaly detector Subspace RX (SSRX), a version of the RX algorithm, has been extensively investigated and its real time implementation performs reasonably well with hyperspectral imagery. However, the problem of false alarms arising at the boundaries between different backgrounds yet needs to be addressed. We consider two paths to the solution: virtual imagery rotation to change the scanning direction and introduction of latency into the data processing. The former approach is based on analysis of the detection result's dependence on the orientation of background boundaries relative to the scanning direction. The latter approach enables incorporation of various background statistics before detection reaches the boundary. Performance of improved SSRX is investigated using collected and simulated hyperspectral imagery.