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http://dx.doi.org/10.7780/kjrs.2009.25.2.145

A Study on Optimal Shape-Size Index Extraction for Classification of High Resolution Satellite Imagery  

Han, You-Kyung (Department of Civil&Environmental Engineering, Seoul National University)
Kim, Hye-Jin (Department of Civil&Environmental Engineering, Seoul National University)
Choi, Jae-Wan (Department of Civil&Environmental Engineering, Seoul National University)
Kim, Yong-Il (Department of Civil&Environmental Engineering, Seoul National University)
Publication Information
Korean Journal of Remote Sensing / v.25, no.2, 2009 , pp. 145-154 More about this Journal
Abstract
High spatial resolution satellite image classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, the extraction of the spatial information is one of the most important steps in high resolution satellite image classification. This study proposes a new spatial feature extraction method, named SSI(Shape-Size Index). SSI uses a simple region-growing based image segmentation and allocates spatial property value in each segment. The extracted feature is integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a SVM(Support Vector Machines) classifier. In order to evaluate the proposed feature extraction method, KOMPSAT-2 and QuickBird-2 data are used for experiments. It is demonstrated that proposed SSI algorithm leads to a notable increase in classification accuracy.
Keywords
Classification Accuracy; High Resolution Satellite Image; Spatial Feature Extraction; SSI(Shape-Size Index);
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