Tree-structured wavelet decomposition based on the maximization of Fisher´s distance

Author

Barbarossa, Sergio ; Parodi, Laura

Author_Institution

INFOCOM Dept., Rome Univ., Italy

Volume

4

fYear

1995

fDate

9-12 May 1995

Firstpage

2523

Abstract

The authors propose a method for optimizing the decomposition law of a tree-structured wavelet transform in order to maximize the capability of discriminating different textures. The optimization criterion is the maximization of the Fisher´s distance. The analysis is carried out theoretically and by simulation on Gaussian Markov random fields and is then applied to the classification of real synthetic aperture radar images

Keywords

Gaussian processes; Markov processes; image classification; image texture; information theory; matrix algebra; optimisation; radar imaging; random processes; synthetic aperture radar; trees (mathematics); wavelet transforms; Fisher´s distance maximization; Gaussian Markov random fields; decomposition law; image classification; optimization criterion; real synthetic aperture radar images; simulation; texture discrimination; tree-structured wavelet decomposition; tree-structured wavelet transform; Analytical models; Computational modeling; Data mining; Feature extraction; Image analysis; Markov random fields; Mirrors; Optimization methods; Synthetic aperture radar; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.480062

Filename

480062