Hybrid Detectors for Subpixel Targets

TitleHybrid Detectors for Subpixel Targets
Publication TypeJournal Articles
Year of Publication2007
AuthorsBroadwater J, Chellappa R
JournalPattern Analysis and Machine Intelligence, IEEE Transactions on
Pagination1891 - 1903
Date Published2007/11//
ISBN Number0162-8828
KeywordsACE subpixel algorithm;AMSD subpixel algorithm;hybrid detectors;hyperspectral imagery analysis;physics;statistics;subpixel target detection;subspace detection;object detection;spectral analysis;statistical analysis;target tracking;Algorithms;Artificial In, Automated;Reproducibility of Results;Sensitivity and Specificity;Signal Processing, Computer-Assisted;, Computer-Assisted;Models, Computer-Assisted;Pattern Recognition, Statistical;Image Enhancement;Image Interpretation, Statistical;Numerical Analysis

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.