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[1]CAO Bao,QIN Qi-ming,ZHANG Zi-li,et al.Feature Enhancement Techniques Combined with Object-Oriented Classification Approach[J].Research of Soil and Water Conservation,2008,15(01):135-138.

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Feature Enhancement Techniques Combined with Object-Oriented Classification Approach

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 15 Number of periods: 2008 01 Page number: 135-138 Column: Public date: 2008-02-20

Title:: Feature Enhancement Techniques Combined with Object-Oriented Classification Approach

Author(s):: CAO Bao, QIN Qi-ming, ZHANG Zi-li, MA Hai-jian, QIU Yun-feng; Remote Sensing and Geological Information System Research Institute, Peking University, Beijing 100871, China

Keywords:: feature enhancement; object-oriented; classification

CLC:: TP391.4

DOI:: -

Abstract:: To deal with the contradiction of classical pixel based on classification approaches cannot satisfy the requirements of High Resolution Image (HRI) classification.Feature Enhancement Techniques Combined with Object-Oriented Classification Approach (FETCOOCA) is provided.Considering the difference of the objects in terms of spectrum, shape, texture etc.contained in HRI, some feature enhancement techniques are carried out on the area of water body, vegetation, and constructions.To test the overall accuracy of FETCOOCA classification result image, FETCOOCA is performed using SPOT5 image, which located in Haidian District, Beijing, China.Finally, a comparison between FETCOOCA and classical pixel based classification approaches is carried out.The study proved that: for HRI classification, FETCOOCA has much better classification result than classical pixel based classification approaches.It can significantly improve the overall classification accuracy of HRI, can avoid the pepper and salt phenomena, and have rich syntax information which is easy for image interpretation.

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