Detection technology of foreign matter on the ocean for MDA with hyperspectral imaging

Target detection using hyperspectral images is useful for Maritime Domain Awareness (MDA). For future application to MDA, in the previous study, targets on the sea was photographed with a hyperspectral camera mounted on a helicopter to demonstrate a target detection using a Reed-Xiaoli detector (RXD). Although the demonstration turned out to be successful, for there were many erroneous detections due to white waves, improvement of the detection accuracy was desired. In this study, pixels classified as white waves by random forest, which is a supervised machine learning method, were removed from pixels which were regarded as anomaly by RXD.As a result, 76% white waves were successfully removed. This study show that white wave removal is possible by machine learning. This will improve the detection accuracy of foreign matter on the ocean.