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7 November 2008Feature extraction and scale analysis based on Quickbird image using object-oriented approach
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.
Yina Qi,Fang Huang, andXin Qi
"Feature extraction and scale analysis based on Quickbird image using object-oriented approach", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470R (7 November 2008); https://doi.org/10.1117/12.813228
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Yina Qi, Fang Huang, Xin Qi, "Feature extraction and scale analysis based on Quickbird image using object-oriented approach," Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470R (7 November 2008); https://doi.org/10.1117/12.813228