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Reseach Article

Classification of High Resolution Urban satellites Images using SVM and Haralick Features with a Hybrid Median Filter

Published on September 2012 by Aissam Bekkari, Soufian Idbraim, Azeddine Elhassouny, Driss Mammass, Mostapha El Yassa, Danielle Ducrot
Software Engineering, Databases and Expert Systems
Foundation of Computer Science USA
SEDEX - Number 1
September 2012
Authors: Aissam Bekkari, Soufian Idbraim, Azeddine Elhassouny, Driss Mammass, Mostapha El Yassa, Danielle Ducrot
e65b17f8-d601-4af7-a04b-93f8e71446be

Aissam Bekkari, Soufian Idbraim, Azeddine Elhassouny, Driss Mammass, Mostapha El Yassa, Danielle Ducrot . Classification of High Resolution Urban satellites Images using SVM and Haralick Features with a Hybrid Median Filter. Software Engineering, Databases and Expert Systems. SEDEX, 1 (September 2012), 35-40.

@article{
author = { Aissam Bekkari, Soufian Idbraim, Azeddine Elhassouny, Driss Mammass, Mostapha El Yassa, Danielle Ducrot },
title = { Classification of High Resolution Urban satellites Images using SVM and Haralick Features with a Hybrid Median Filter },
journal = { Software Engineering, Databases and Expert Systems },
issue_date = { September 2012 },
volume = { SEDEX },
number = { 1 },
month = { September },
year = { 2012 },
issn = 0975-8887,
pages = { 35-40 },
numpages = 6,
url = { /specialissues/sedex/number1/8356-1007/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Software Engineering, Databases and Expert Systems
%A Aissam Bekkari
%A Soufian Idbraim
%A Azeddine Elhassouny
%A Driss Mammass
%A Mostapha El Yassa
%A Danielle Ducrot
%T Classification of High Resolution Urban satellites Images using SVM and Haralick Features with a Hybrid Median Filter
%J Software Engineering, Databases and Expert Systems
%@ 0975-8887
%V SEDEX
%N 1
%P 35-40
%D 2012
%I International Journal of Computer Applications
Abstract

The classification of remotely sensed images knows a large progress taking in consideration the availability of images with different resolutions as well as the abundance of classification's algorithms. A number of works have shown promising results by the fusion of spatial and spectral information using Support vector machines (SVM). For this purpose, we propose a methodology exploiting a composite kernel that easily combines multi-spectral features, Haralick texture features and Hybrid Median Filter, with different window sizes. The proposed approach was tested on common scenes of urban imagery. The result shows that the combined use of spectral and texture information together significantly improved the accuracy of satellite image classification.

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Index Terms

Computer Science
Information Sciences

Keywords

Svm Composite Kernels Haralick Features Hybrid Median Filter Satellite Image Spectral And Spatial Information Glcm