基于小波变换的多方位角SAR图像融合方法

针对目标散射特性空变效应以及多方位角图像信息冗余的问题,提出了一种基于小波变换和边缘检测的多方位角SAR图像融合方法。首先,将图像进行小波变换,完成低频信息和高频信息的分离,实现图像的多分辨表征及序贯图像多方位角信息的融合;然后,利用改进的Robinson算子增强图像的轮廓特征;最后,融合实验和定量评估结果证明了本文所提融合方法的有效性。

Multi-aspect SAR image fusion method based on wavelet transform

Considering the diversity of target scattering characteristics with different observation angle and information redundancy of multi-aspect images,this paper proposes a novel multi-aspect SAR image fusion method based on wavelet transform and edge detection.First,wavelet transform was performed to multi-aspect space-borne SAR image processing.The images were separated to different parts of frequency so that the multiresolution representation and multi-aspect information of sequential images can be conveniently fused.Second,the improved Robinson edge detection algorithm was used to strengthen the energy of contour feature.Finally,fusion experiment and quantitative evaluation method were used to verify the effectiveness of this fusion imaging method.