The adaptive coherence estimator: a uniformly most-powerful-invariant adaptive detection statistic
IEEE Transactions on Signal Processing
The CFAR adaptive subspace detector is a scale-invariant GLRT
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive threshold estimation via extreme value theory
IEEE Transactions on Signal Processing
A novel sub-pixel edge detection for micro-parts manipulation
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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Subpixel detection is a challenging problem in hyperspectral imagery analysis. Since the target size is smaller than the size of a pixel, detection algorithms must rely solely on spectral information. A number of different algorithms have been developed over the years to accomplish this task, but most detectors have taken either a purely statistical or a physics-based approach to the problem. We present two new hybrid detectors that take advantage of these approaches by modeling the background using both physics and statistics. Results demonstrate improved performance over the well known AMSD and ACE subpixel algorithms in experiments that include multiple targets, images, and area types -- especially when dealing with weak targets in complex backgrounds.