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《Land and Resources Informatization》 2009-05
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Application of Supervised Classification and Visual Revision in High Resolution Remote Sensing Image

Chen Chao~1,Jiang Tao~(1,2),Yue Yuanping~3 (1.Department of Remote Sensing Science and Technology,College of Geomatics,Shandong University of Science and Technology,Qingdao,Shandong,266510 2.Shandong Provincial Key Laboratory of Fundamental Geography and Digital Technology,Shandong University of Science and Technology,Qingdao,Shandong,266510 3.No.94362 of PLA,Chengyang District,Qingdao,Shandong,266111)  
Using computer to recognize the type of the ground object on the remote sensing image is an important part of the remote sensing digital image processing.The traditional classification of ground object generally uses remote sensing images,such as MSS,TM and Spot,as data source.Compared with MSS, TM,Spot and other traditional remote sensing images,QuickBird and other high-resolution images have advantages of larger amount of data,reduced mixed-pixel,and increased ground object information,and therefore can be used in the land classification.In the supervised classification,the method of reselecting the training zone is usually adopted to revise the template of which the precision is not high enough.But in this paper,we use the visual revision method to supplement the supervised classification.This method can correct the error and the mixed classification of the ground object in the initial classification brining the ground object back to the correct classification,and significantly improve the accuracy of the land classification.To verify the effectiveness of the algorithm,the experiment and accuracy assessment are carried out using ERDAS IMAGING remote sensing image processing software.The experimental results show that the image classification accuracy can be greatly improved by using the ground object classification method which combines the supervised classification and visual revision.
【CateGory Index】: P237
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