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Analysis of the Mutli-scale Characteristics with Objects Extraction |
HUANG Hui-ping1,2, WU Bing-fang1
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(1.Institute of Remote Sensing Applications,Chinese Academic of Sciences,Beijing,China, 100101;2.South China Normal University,Guangzhou510063,China) |
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Abstract Image information with different scale displays distinct spatial structure. Scale is different for each remote sensing image analysis. Image analysis with single scale could not meet the heterogeneity and dynamic of pattern and process and objects extraction in the same resolution or scale is unreasonable. To acquire the high quality data of the surface, multi-scale image analysis is necessary. Object-oriented image analysis approach offers a solution to extract different objects from various scale images. Object-oriented image analysis creates meaningful objects and builds a hierarchy levels close to surface character using multi-scale segmentation. Objects could be analysed in their suitable scale levels. The patient advantage of this method is obvious that classification is based on the meaning objects, rather on the pixels. In object- oriented image analysis“scale”is not the pixel size, but the segmentation scale threshold. This paper presents a snapshot of work using multi-scale image analysis with several resolution images. The results show the characteristics of objects multi-scale analysis, the relationship of spatial scale and resolution.
Image object levels from multi-scale segmentation are different from other images with various spatial resolutions. Different objects in surface could be represented in corresponding image object levels. Context information and texture information are very important factors for image information extraction.
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Received: 28 February 2003
Published: 24 November 2011
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