基于区域分割的NSCT域SAR与全色图像融合算法

Fusion algorithm of SAR and panchromatic images based on region segmentation in NSCT domain

提出了一种基于多阈值分割和无下采样Contourlet变换(nonsubsampled Contourlet transform,NSCT)的SAR与全色图像融合算法。首先对降斑SAR图像作多阈值分割,并定义了区域均值比量测算子将SAR图像进行区域划分;然后采用NSCT对降斑SAR图像和全色图像进行多尺度、多方向分解,分解后的低频部分根据区域均值比量测算子进行区域融合,高频部分则采用区域与窗口邻域相结合的融合策略;最后对融合系数进行重构得到融合图像。实验结果表明,该算法的融合图像既可保持全色图像的空间分辨率,又可有效获取SAR图像的目标信息,融合效果优于小波变换法以及基于像素的NSCT法。

An fusion algorithm for synthetic aperture radar（SAR） and panchromatic images based on multi-level threshold segmentation and the nonsubsampled Contourlet transform（NSCT） is proposed.Firstly,multi-level threshold segmentation is done for the despeckle SAR image,and the measurement named ratio of region mean（RRM） is presented to divide the SAR image into several regions.Then the NSCT is performed on the despeckle SAR image and the panchromatic image at different scales and directions.The low-frequency coefficients are fused with the region-based fusion scheme according to the RRM,and the high-frequency coefficients are fused with the windows-based rules and region-based rules.Finally the fused coefficients are reconstructed to obtain the fused image.Experimental results show that the fused image can not only preserves the spatial resolution of the panchromatic image but also effectively join the target information of the SAR image.The algorithm performs significantly better than the wavelet transform and the pixel-based NSCT.