A Semiparametric Model for Hyperspectral Anomaly Detection
Figure 9
QG-SemiP results testing Cube 2 (a) for scene anomalies; output surface (b) was produced using ; output surface (c) was produced using . Bright pixel values (white) in the output surfaces correspond to values above the probabilistic cutoff threshold —depicting the highest confidence level of anomaly presence in the imagery, relative to randomly selected blocks of data. Testing procedure was independently repeated times, as highlighted in Figure 8. Using the available ground truth information of the scene, the white clusters in the far right figure cover about 90% of the motor vehicles (the targets) and no false alarms.
