Applying ordered statistics filters for point target detection in hyperspectral data Conference Paper uri icon

abstract

  • In this paper, we apply highly ordered statistics filters to hyperspectral data to enable the detection of anomalous targets whose signatures are known. Each frame has subtracted from it an estimate based on an ordered statistics filter; the resulting frames are then combined optimally based on the covariance data of the cube and the spectral signature of the target. We show that the effect of the ordered statistic filter is to eliminate false alarms at edge points.

publication date

  • January 1, 2004