Point target detection in segmented images Academic Article uri icon

abstract

  • To perform point target acquisition in multispectral and hyperspectral images, it is often advantageous to compare the signature of the investigated pixel to a known target signature. To do this properly, it is necessary to estimate the expected mean and covariance matrix of an investigated pixel in a particular location, based on its local surroundings. The degree to which this pixel signature differs from the estimated background then becomes the data, which is matched to the desired target signature. The standard method for such an analysis is the RX algorithm of Reed and Yu. The mean is normally estimated from the local environment of the pixel; the covariance matrix can either be estimated globally or in some local window. In recent research, we have considered how to improve the algorithm by eliminating edge points as potential false alarms. In the present work, a prior …

publication date

  • October 15, 2004