Title :
Subset selection analysis for the reduction of hyperspectral imagery
Author :
Vélez-Reyes, Miguel ; Jiménez, Luis O.
Author_Institution :
Dept. of Electr. & Comput. Eng., Puerto Rico Univ., Mayaguez, Puerto Rico
Abstract :
Presents the formulation of the dimension reduction problem using subset selection as a matrix approximation problem. A heuristic algorithm to solve this problem is presented. Numerical results using LANDSAT and AVIRIS images show that the selected bands are contained in a space that is almost aligned with the first few principal components
Keywords :
image processing; remote sensing; AVIRIS images; LANDSAT images; dimension reduction problem; heuristic algorithm; hyperspectral imagery reduction; matrix approximation problem; numerical results; principal components; subset selection analysis; Covariance matrix; Hyperspectral imaging; Hyperspectral sensors; Image analysis; Image processing; Laboratories; Random variables; Remote sensing; Satellites; Vectors;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.691622
