UNSUPERVISED CHANGE DETECTION FOR REMOTE SENSING IMAGES USING MULTISCALE DECOMPOSITION AND TREELET FUSION : A LEVEL SET APPROACH
With the development of remote sensing technology, using remote sensing images to do change detection is gaining more and more attention. In this paper, a novel approach for unsupervised change detection is proposed.Firstly, SWT is used for multi-scale decomposition; then use treelet to fusion the reconstructed difference images at every level; finally, the change detection map is obtained through a level set segmentation. The effectiveness of our method is validated by experiments on five different data sets from different resources. By comparing with other state-of-art technologies, the results show that the proposed method yields better performance in most cases.
change detection multi-scale decomposition treelet level set segmentation
Guiting Wang Min Zhang Xiaolin Tian LC Jiao
Key laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of Chi Key laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of Chi
国际会议
2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)
成都
英文
1558-1561
2011-10-24（万方平台首次上网日期，不代表论文的发表时间）