基于邻域重构模型的高分辨SAR图像精确配准

合成孔径雷达(SAR)的成像过程使其高分辨图像的几何形变呈现局部性.针对高分辨SAR图像精确配准问题,本文提出一种基于邻域重构模型的局部转换函数.邻域重构模型首先采用重构系数刻画参考图像中每个像素点的几何位置;接着给出了一种重构控制点的选择标准使每个像素的配准误差达到最小;最后根据重构系数及控制点坐标对输入图像进行再抽样以实现配准.与经典分片线性映射相比,该模型从理论上给出了一种区域剖分准则:对于每个像素选取能使配准误差能达到最小的控制点作为重构控制点.对模拟数据和真实SAR图像进行了试验,结果表明,该模型能有效地提高配准精度.

Accurate Registration of High Resolution SAR Images Base on Neighborhood Reconstruction Model

For the accurate registration of high resolution Synthetic Aperture Radar (SAR) images, local transformation functions are preferable to global ones. In this paper, a local mapping model, namely neighborhood reconstruction model, was presented to fit the geometric distortions in SAR image registration. First, each point in the reference image was characterized by the neighboring Control Points (CP) with reconstruction weights. Then, a criterion for neighboring CP selection was proposed to minimize registration error at each point. Finally, the associated point in the sensed .image was resampled according to the geometric distortions and the reconstruction weights. The theoretical support from neighborhood reconstruction model to the classical piecewise linear approach was also presented. Experiments on both simulation data and real high resolution SAR images show that the registration accuracy is improved.