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Scale effect and optimal scale in object-oriented information extraction of high spatial resolution remote sensing image

ZHANG Jun①,ZHU Guo-long②,LI Yan②(①No.3 Topographic Survey Team of SBSM,Harbin 150081,China;②Jiangsu Key Laboratory of Resources and Environmental Information Engineering /China University of Mining and Technology,Xuzhou 221008,China)  
From scale effect problem in the remote sensing information extraction,the targets'fractal dimensions,compact ratio,areas,mean value,standard deviation and mean differential to neighbors of image objects were experimental researched in the paper.It found that these index values of all targets would fluctuate with scales,and different targets in the images have different feature values and scales.It is necessary to extract the region of interest in optimal scale images.In view of this,RMAS method was developed,according to the best classification principle as "homogeneity in class,heterogeneity between classes".The thought of this method was that the heterogeneity in class is the minimum and is the maximum between classes when RMAS is the maximum,so the segmentation scale is optimal.According to the principle of the highest information extraction accuracy based on the optimal scale,the experiment verified the feasibility of this method and the classification result was better.
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