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Proceedings Paper

Feature extraction and scale analysis based on Quickbird image using object-oriented approach
Author(s): Yina Qi; Fang Huang; Xin Qi
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Paper Abstract

Information extraction from high-resolution remote sensing image automatically has been attracting wide audience globally nowadays. Traditional pixel-based classification for remote sensing image with high spatial resolution is out need of precision. Considering of the characteristic of remote sensing, object-oriented approach gives the resolution. Taking Quickbird image as an example, we extract some typical urban targets from the image using object-oriented image analysis in this study. The most suitable scale of image segmentation is also discussed. We also evaluate the classification precision in associated with different segmentation scale. Result shows that object-oriented approach has a great deal of advantage such as high precision, high efficiency, convenience and so on. When the segmentation scale is defined between 15 and 20, we will get the best classification result. Extracting at the most suitable scale of image segmentation, the precision of classification can reach above 90 percent.

Paper Details

Date Published: 7 November 2008
PDF: 9 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470R (7 November 2008); doi: 10.1117/12.813228
Show Author Affiliations
Yina Qi, Northeast Normal Univ. (China)
Fang Huang, Northeast Normal Univ. (China)
Xin Qi, Northeast Normal Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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