An Automatic Thresholding Method For Water Body Detection From SAR Image

This paper presents a water body detection framework with an automatic threshold determination procedure. Water bodies in SAR image often appear dark and homogeneous due to specular reflection. Therefore, the water bodies can easily be detected with a thresholding method. However, the threshold needs to be adjusted interactively for every SAR data due to backscatter differences between water bodies in SAR data. The recursive Otsu thresholding method is used to determine the threshold automatically. The normalized between-class variance is introduced to select optimal threshold from threshold set generated by the recursive Otsu thresholding. The presented framework eliminates the manual operating interaction and has a near-real-time capability in extracting water bodies from huge amounts of data. Experimental results with TerraSAR-X stripmap data verify the effectiveness of the framework.