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Remote Sensing Technology and Application  2012, Vol. 27 Issue (4): 536-541    DOI: 10.11873/j.issn.1004-0323.2012.4.536
    
A Study on Object-oriented Remote Sensing Image Classification based on Image Cognition and Geographical Understanding
Zhu Chaohong,Liu Yong
(College of Earth and Environmental Science,Lanzhou University,Lanzhou 730000,China)
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Abstract  

Taking remote sensing image cognition and geographical understanding as the main analytic perspective,this paper firstly explored the characteristics of the image objects spectral,shape,textural and semantic by the multi-scale segmentation,to determine the corresponding relations between the characteristic information of the object and the ground.And then,this study rationally selected some classification features and built classification rules.Finally,multiple level classifications were carried out hierarchically to extract information of the interested objects in the study area.The result showed that the selected features in classification rules not only can effectively extract information,but also had the explicit geographical significance.Compared with the traditional pixel-based maximum likelihood classification methods,the classification accuracy of the new method was improved significantly.

Key words:  Object-oriented method      Multi-scale segmentation      Image cognition      Geographical understanding     
Received:  12 May 2011      Published:  24 August 2012
TP 75  
  TP 79  
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Cite this article: 

Zhu Chaohong,Liu Yong. A Study on Object-oriented Remote Sensing Image Classification based on Image Cognition and Geographical Understanding. Remote Sensing Technology and Application, 2012, 27(4): 536-541.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2012.4.536     OR     http://www.rsta.ac.cn/EN/Y2012/V27/I4/536

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