Generic wavelet-based hyperspectral classification applied to vegetation stress detection

Author

Kempeneers, Pieter ; Backer, Steve De ; Debruyn, Walter ; Coppin, Pol ; Scheunders, Paul

Author_Institution

Flemish Inst. for Technol. Res., Belgium

Volume

43

Issue

3

fYear

2005

fDate

3/1/2005 12:00:00 AM

Firstpage

610

Lastpage

614

Abstract

This communication studies the detection of vegetation stress in hyperspectral data. Compared to traditional vegetation stress indices, the proposed approach uses the complete reflectance spectrum and its wavelet representation. The detection strategy is formulated as a classification problem. Experiments are conducted on fruit tree stress detection. The experiments show the superior performance of the proposed strategy and demonstrate its generic nature.

Keywords

feature extraction; geophysical signal processing; image classification; multidimensional signal processing; object detection; vegetation mapping; wavelet transforms; classification problem; feature extraction; fruit tree stress detection; hyperspectral data; hyperspectral remote sensing; reflectance spectrum; vegetation stress detection; wavelet representation; wavelet transform; wavelet-based hyperspectral classification; Classification tree analysis; Crops; Hyperspectral imaging; Hyperspectral sensors; Laboratories; Optical scattering; Reflectivity; Remote sensing; Stress; Vegetation;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/TGRS.2004.839545

Filename

1396333