Automatic Matching of Optical and SAR Imagery through Shape Property

作者：Ye Yuanxin; Shen Li^*; Wang Jicheng; Li Zhipeng; Xu Zhu

来源：IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015-07-26 to 2015-07-31.

• image matching
• DLSS
• similarity metric
• SAR

Automatic matching of optical and SAR images could be challenging due to the significant non-linear intensity differences caused by radiometric variations among such images. To address this problem, this paper utilize the Shape Property to detect the correspondences between images. A new shape descriptor is first built on the basis of the local self-similarity descriptor. Then, the normalized correlation coefficient of the descriptor is used as the similarity metric (named DLSS), which represents the shape similarity among images. Finally, a template-matching strategy is applied to achieve the correspondences between images. The proposed method has been evaluated with four pairs of optical and SAR images. The experimental results demonstrate that the proposed method is robust to non-linear intensity differences, and improves the matching performance compared with the state-of-the-art methods.

• 出版日期2015
• 单位西南交通大学