A Semiparametric Model for Hyperspectral Anomaly Detection
Figure 7
The relationship between (the number of randomly selected blocks of data, shown as yellow squares on the imagery) and the contamination probability is shown in (b) for a given (e.g., ), which is an upper bound guess representing the maximum ratio between target pixels over the area. To better characterize the unknown clutter background, a high is most desired, but at a high cost, that is, an undesirably high . The overall contamination probability, however, can significantly decrease by independently repeating the random sampling process number of times, as shown (c) of figure, and then fusing results using a suitable method.
