Title :
Feature extraction of hyperspectral data using the Best Wavelet Packet Basis
Author :
Hsu, Pai-Hui ; Tseng, Yi-Hsing
Author_Institution :
Dept. of Surveying Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
An adaptive wavelet decomposition algorithm called the Best Wavelet Packet Basis is used to extract the most useful spectral features from the original hyperspectral data for classification applications. Tested on a set of AVIRIS data, the novel feature extraction method is evaluated and compared with some contemporary feature extraction methods.
Keywords :
adaptive signal processing; feature extraction; geophysical signal processing; geophysical techniques; image classification; multidimensional signal processing; remote sensing; terrain mapping; vegetation mapping; wavelet transforms; AVIRIS; Best Wavelet Packet Basis; IR; adaptive wavelet decomposition algorithm; best wavelet packet basis; feature extraction; geophysical measurement technique; hyperspectral remote sensing; image classification; image processing; infrared; land surface; multispectral remote sensing; spectral features; terrain mapping; vegetation mapping; visible; Cost function; Data mining; Feature extraction; Fourier transforms; Hyperspectral imaging; Hyperspectral sensors; Libraries; Time frequency analysis; Wavelet packets; Wavelet transforms;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026215
