Title :
Detection of ephemeral changes in sequences of images
Author :
Theiler, James ; Adler-Golden, Steven M.
Author_Institution :
Space & Remote Sensing Sci., Los Alamos Nat. Lab., Los Alamos, NM
Abstract :
The formalism of anomalous change detection, which was developed for finding unusual changes in pairs of images, is extended to sequences of more than two images. Extended algorithms based on RX, Chronochrome, and Hyper are presented for identifying the most anomalously changing pixels in a sequence of co-registered images. Experimental comparisons are performed both on real data with real anomalies and on real data with simulated anomalies.
Keywords :
image sequences; anomalous change detection; ephemeral changes; image sequences; Algorithm design and analysis; Change detection algorithms; Detectors; Gaussian distribution; Laboratories; Lighting; Machine learning; Machine learning algorithms; Pixel; Remote sensing;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, 2008. AIPR '08. 37th IEEE
Conference_Location :
Washington DC
Print_ISBN :
978-1-4244-3125-0
Electronic_ISBN :
1550-5219
DOI :
10.1109/AIPR.2008.4906469
