Feature extraction and scale analysis based on Quickbird image using object-oriented approach

Yina Qi; Fang Huang; Xin Qi

doi:10.1117/12.813228

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7 November 2008 Feature extraction and scale analysis based on Quickbird image using object-oriented approach

Yina Qi; Fang Huang; Xin Qi

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Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470R (2008) https://doi.org/10.1117/12.813228
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

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.

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Yina Qi, Fang Huang, and 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

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