Title :
A robust variation of the principle components algorithm
Author :
Haberstroh, Richard ; Madonna, Richard
Author_Institution :
Res. & Dev. Center, Northrop Grumman Corp., Bethpage, NY, USA
Abstract :
Discusses two remote sensing image classifiers for hyperspectral data that are relatively insensitive to small errors in the atmospheric transmission function. These classifiers permit the authors to use laboratory measured spectral databases for classification of unknown spectra. Numerical results are presented that demonstrate that the classifiers have a better than 90% identification accuracy even when using the “wrong” atmospheric transmission function
Keywords :
geophysical signal processing; geophysical techniques; image classification; optical information processing; remote sensing; atmospheric transmission function; geophysical measurement technique; hyperspectral; image classification; land surface; multispectral remote sensing; optical imaging; principle components algorithm; robust variation; terrain mapping; visible infrared IR; Atmospheric measurements; Atmospheric modeling; Building materials; Classification algorithms; Hyperspectral imaging; Hyperspectral sensors; Image databases; Laboratories; Layout; Meteorology; Remote sensing; Robustness;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location :
Firenze
Print_ISBN :
0-7803-2567-2
DOI :
10.1109/IGARSS.1995.521722
