SAR图像与光学图像多子区鲁棒匹配算法

Robust Algorithm of Matching SAR Image to Optical Image Using Multiple Subarea

提出了一种新的低空机载合成孔径雷达(SAR)图像与卫星光学图像的多子区匹配算法.算法中,依据SAR图像噪声特性,提出了用于SAR图像边缘提取的基于小波包变换的改进断面检测法.匹配中将低空SAR图像分为多个子区,利用子区影像频谱直方图等特性参量判别其可匹配性,并用各子区位置分布关系约束匹配结果.匹配搜索策略为基于提升小波的金字塔分层搜索.用低空SAR图像与SPOT-5卫星光学基准图进行了实验,结果表明该方法的有效性.

A novel algorithm of scene matching with spatial relation constrain was presented. The edge feature of SAR image was extracted via an improved contour detecting algorithm, which computed the gradient of pixels using wavelet packet transform. The real-time image was divided into multiple subarea and each subarea was evaluated by the gray level standard deviation and the distance of spectral histogram. The spatial relationship of the subarea was applied to correct the matching result. The multiple-layer search strategy based on lifting wavelet transform was used to improve the performance of the algorithm. The experiment result shows that the algorithm is effective and robust.