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

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IJCA Special Issue on Software Engineering, Databases and Expert Systems
© 2012 by IJCA Journal
SEDEX - Number 1
Year of Publication: 2012
Authors:
Aissam Bekkari
Soufian Idbraim
Azeddine Elhassouny
Driss Mammass
Mostapha El Yassa
Danielle Ducrot

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

@article{key:article,
	author = {Aissam Bekkari and Soufian Idbraim and Azeddine Elhassouny and Driss Mammass and Mostapha El Yassa and Danielle Ducrot},
	title = {Article: Classification of High Resolution Urban satellites Images using SVM and Haralick Features with a Hybrid Median Filter},
	journal = {IJCA Special Issue on Software Engineering, Databases and Expert Systems},
	year = {2012},
	volume = {SEDEX},
	number = {1},
	pages = {35-40},
	month = {September},
	note = {Full text available}
}

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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