Hyperspectral Measurements for Ship Detection Using Airborne Image Data

The Remotely sensed satellite or airborne images can aid rapid vessel monitoring over wide areas at high resolutions. In this study, airborne hyperspectral experiments were performed to detect marine vessels mainly including fishing boat and yacht by applying pixel-based mixture techniques and to estimate the size of the vessels through an objective ellipse fitting method. Several hyperspectral mixture algorithms, such as N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA), were used for the detection of vessels. The pixel-based probability of detection (POD) and false alarm ratio (FAR) for all 14 vessels were 96.40% and 4.30%, respectively. Compared with the digital mapping camera (DMC) images with resolutions of 0.10 m, the root-mean-square error of the length and width of the vessels were approximately 1.19 m and 0.81 m, respectively.