基于Sentinel-1双极化数据改进水体提取的Otsu算法

基于SAR图像的阈值分割法是水体信息有效提取的常用方法之一。针对Otsu算法对于SAR影像水体提取精度低、噪声大的问题，以C波段Sentinel-1 SAR为数据源，提出一种基于Otsu算法的SAR图像水体提取新方法。该方法首先基于双极化数据构建自然指数函数，优化原始Sentinel-1数据图像像元直方图分布，再结合Otsu算法对图像进行水体提取，最后基于DEM数据去除误提取的山体阴影。以同一天的Landsat 8光学影像作为真实水体样本进行精度评定，结果表明：在不同水体占比情况下，该方法水体提取精度均优于Otsu算法，在水体占比小于10%时综合精度提升约为20%—60%，而且噪声小、适用性强，可用于快速高效获取大范围内水体信息。

Improved Otsu Algorithm for Water Extraction based on Sentinel-1 Dual-polarization Data

Threshold segmentation method based on SAR image is one of the commonly used methods for effective extraction of water information. In view of the problem of low accuracy and high noise for water extraction on SAR image by Otsu algorithm， a new method based on Otsu algorithm is proposed using C-band Sentinel-1 SAR as the data source. This method constructs natural exponential function based on dual-polarization data to optimize the histogram distribution of pixels in original Sentinel-1 image firstly， and then combines Otsu algorithm to extract water information from image， at last removes the wrongly extracted hill shade based on DEM. The accuracy is evaluated by using optical images of Landsat 8 as the real water information. The results show that the accuracy of water extraction for the proposed method is superior to traditional Otsu algorithm in the case of different water proportions， accuracy of which increased by about 20—60% while water proportion less than 10%. Moreover， this proposed method has low noise and wide applicability features， which can be used for obtaining water information of large area quickly and efficiently.