An Improved Multi-Image Matching Method in Stereo-Radargrammetry
Hao Ding, Jixian Zhang, Guoman Huang, Jianjun Zhu · IEEE Geoscience and Remote Sensing Letters · 2017
The new generation of synthetic aperture radar (SAR) sensors provides us with an opportunity to match multiple high-resolution SAR images. Moreover, the multiple SAR image matching methods have recently gained a lot of attention due to the fact that they can obtain more accurate, better distributed, and more reliable matches than the stereo matching methods. In this letter, we present an improved multi-image matching method to simultaneously identify matches from multiple SAR amplitude images. The proposed method makes better use of the relationships between the pixels in the deformed correlation window and integrates geometric and radiometric information from multiple SAR images. Experiments on Chinese Academy of Surveying and Mapping Synthetic Aperture Radar (CASMSAR) data sets demonstrate that the improved multi-image matching method is capable of providing more accurate and better distributed matches, as well as offering a better multi-image matching solution in stereo-radargrammetry under the conditions of geometric and radiometric distortions, especially in low-texture areas.