针对合成孔径雷达(synthetic aperture radar, SAR)图像变化检测中存在的差异图细节信息丢失的问题,提出了一种面向SAR图像像素级变化检测的去模糊化处理方法。通过对差异图漏检像素点分布的理论分析,提出了一种新型的差异图构造方法,将新型差异图构造方法生成的差异图与经典的像素级差异图构造算法生成的差异图相融合,实现了差异图的边缘去模糊化。以均值比值算法为例,实验结果表明,新型差异图构造方法得到的差异信息与邻域变化检测算法得到的差异信息具有较强的互补性;利用新型差异图构造方法进行去模糊化处理后,得到的差异图在主观上更接近真实地物的变化情况,在客观上变化检测结果的漏检数降低,变化检测的精度有所提高。

In order to solve the problem about the loss of detail information of difference maps in the change detection of synthetic aperture radar (SAR) images, a deblurring processing method for the pixel level change detection of SAR images is proposed. Based on the theoretical analysis of the distribution of pixels missed from the difference map, a new method for constructing the difference map is proposed. The difference map generated by this proposed algorithm is fused with the difference map generated by the classical pixel-level change detection algorithm to realize the edge deblurring of the difference map. Taking the average ratio algorithm as an example, the experimental results show that the difference information obtained by the proposed algorithm and that by the neighborhood change detection algorithm are highly complementary. The difference map generated from deblurring by the proposed algorithm is subjectively closer to the change of the real ground object. Objectively, the numbers of the missed points of change detection results are reduced, and the accuracy of change detection is improved.