Abstract: In view of the mainstream object-based classification method in remote sensing image processing using range is not clear, based on e-Cognition software, the standard data set is processed. Comprehensively considering the visual effects, overall accuracy and user accuracy, classification results and precision analysis of mainstream object-based classification are systematic analysis in the high resolution image. The experimental results show that there are mixed phenomena using different classification methods and the mixed objects are not exactly the same. In dealing with the same standard data set, the membership function has the highest accuracy but the slowest speed. The classification effect of Bayes is the worst, but the operation is simple. The classification speed of SVM, RF, DT are faster and have higher accuracy. Meanwhile SVM has obvious advantages in distinguishing objects with high similarity. In the selection of high resolution image classification method, we should fully consider the feature selection of classified images to select the appropriate classification method.

Key words: object-based classification, SVM classification, RF classification, DT classification, Bayes classification, membership function classification