Optimizing wavelets for hyperspectral image classification

Author

Daamouche, Abdelhamid ; Melgani, Farid ; Hamami, Latifa

Author_Institution

Dept. of Inf. Eng. & Comput. Sci., Univ. of Trento, Trento, Italy

Volume

2

fYear

2009

fDate

12-17 July 2009

Abstract

This work presents a procedure to optimize a wavelet filter in terms of discrimination capability between the classes characterizing a given hyperspectral remote sensing image. To this end, this procedure estimates the coefficients of the wavelet filter bank by means of a particle swarm optimization (PSO) so that to maximize the average Bhattacharyya distance. The obtained experimental results show that PSO-based optimized wavelets can significantly outperform conventional wavelets.

Keywords

geophysical image processing; image classification; particle swarm optimisation; remote sensing; wavelet transforms; average Bhattacharyya distance; hyperspectral image classification; hyperspectral remote sensing image; particle swarm optimization; wavelet filter bank; wavelet optimization; Discrete wavelet transforms; Filter bank; Finite impulse response filter; Hyperspectral imaging; Hyperspectral sensors; Image classification; Low pass filters; Particle swarm optimization; Remote sensing; Support vector machines; hyperspectral images; image classification; particle swarm optimization (PSO); support vector machine (SVM); wavelet filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009

Conference_Location

Cape Town

Print_ISBN

978-1-4244-3394-0

Electronic_ISBN

978-1-4244-3395-7

Type

conf

DOI

10.1109/IGARSS.2009.5418070

Filename

5418070