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《Science of Surveying and Mapping》 2014-08
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Object oriented remote sensing image classification based on segmenting and merging

LIU Xiao-li;Troops 61206;  
The result of traditional remote sensing image classification method based on spectral features has salt and pepper noise and poor accuracy,while the object-oriented classification method has higher precision for it contains texture feature and spatial structure information besides spectral information.However,the existing classification methods ignore spatial information.In this paper,a remote sensing image classification method of spectral information and spatial information segmenting and merging based on object-oriented was put forward;the classification accuracy was tested with confusion matrix and compared with maximum likelihood classification method.Results showed that this method could remove salt and pepper noise and avoid the matter of‘same spectral from different materials' and‘same material with different spectral',which improved the classification accuracy and reliability.
【CateGory Index】: TP751
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