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30 October 2009 A multiscale analysis method on QuickBird multispectral image
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Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74981S (2009)
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Earth's surface space is a complex huge system and character with hierarchical structures. Entities, patterns and processes all show inherent hierarchy structure in nature. The character of Scale-dependence is corresponded with hierarchy. Many research works have demonstrated that scale-dependence is a basic characteristic of Geo-spatial space. Therefore, the multi-scale or hierarchical approach needs to be introduced in the course of spatial information analysis, monitoring, modeling and management. It is well know that image analyze result was influenced by the window size that was selected. The original fixed window cannot suit with the object spatial character. In this letter, we first propose an optimal window selection method, based on the spectral information in a local block region, for choosing the suitable window size adaptively. Secondly, the object spatial information is learned based on the selected optimal window size. Thirdly, both the spectral and spatial information were used in image classification. In this paper, the proposed algorithm can obtain the multi-scale features effectively and the features we get at different scale level have an obvious stability with property. In the experiment on the QuickBird image data, the proposed algorithm clearly improves the classification accuracies than fixed window sizes and reduces the salt and pepper effect and error. It is suitable to form multi-scale hierarchy image-sets and select the objects at different scale levels.
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Weiying Yang, Liangpei Zhang, Hua Liu, and Songtao Yu "A multiscale analysis method on QuickBird multispectral image", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981S (30 October 2009);

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