DocumentCode
3306489
Title
Geometrical features for the classification of very high resolution multispectral remote-sensing images
Author
Luo, Bin ; Chanussot, Jocelyn
Author_Institution
GIPSA-Lab., Grenoble Inst. of Technol., Grenoble, France
fYear
2010
fDate
26-29 Sept. 2010
Firstpage
1045
Lastpage
1048
Abstract
In order to extract geometrical features from a multispectral image and derive a classification, an approach based on the topographic map of the image is proposed. For each pixel, the most significant structure containing it is extracted. The classification of this pixel is based on its spectral information and the geometrical features of the corresponding structure (its area and perimeter). The results obtained on multispectral remote sensing images taken by two different sensors show the efficiency of the extracted geometrical features for separating some classes with very similar spectral attributes but of different semantic meanings.
Keywords
computational geometry; feature extraction; image classification; image resolution; geometrical feature extraction; high resolution multispectral remote sensing image; image classification; pixel; spectral information; topographic map; Accuracy; Buildings; Feature extraction; Pixel; Remote sensing; Roads; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1522-4880
Print_ISBN
978-1-4244-7992-4
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2010.5649890
Filename
5649890
Link To Document