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A multilevel contextual approach is proposed in this paper for change detection of VHR images. By representing the change features in a hierarchical contextual manner, the changes are detected level-by-level. By taking advantages of SVMs, the ambiguity of changes is mitigated and the optimal changes are detected peculiar to the specific user. Compared to the traditional methods, the proposed approach is more accurate, more robust and faster. Experiments demonstrate the effectiveness and advantages of the proposed approach.