基于非下采样Contourlet变换的方向Teager能量的极化SAR图像融合*

提出一种基于非下采样Contourlet变换和方向Teager能量的极化SAR图像融合算法。采用具有多尺度、多方向和平移不变性特点的非下采样Contourlet变换对多个单极化强度图像进行分解，然后高频子带图像分别按行和列进行Teager能量计算，选取Teager能量作为度量来提取区域边缘与纹理信息。对于低频系数采用平均融合算法，根据高频子图Teager能量分布差异，对于方向高频系数采用不同最优加权算法实现极化图像的融合处理。实验结果表明，提出的算法与PWF算法相比在保留原始图像边缘和纹理信息的同时，可以有效地抑制相干斑噪声的影响，取得较好的融合视觉效果。

Fusion of polarimetric SAR image based on nonsubsampled Contourlet transform and directional Teager energy

This paper proposed a fusion method for polarimetric SAR image based on nonsubsampled Contourlet transform and directional Teager energy. It decomposed the several of single-polarimetric-channel SAR intensity images using nonsubsampled Contourlet transform, which had multi-scale, multi-direction and shift-invariant characteristics. Then used the high-frequency sub-band images to calculate Teager energy by rows and columns respectively. Presented the Teager energy to measure and extract region edge and texture information. For the low-pass coefficients, used an averaging fusion rule. According to Teager energy distribution differences in high frequency sub-band images, for the directional high-frequency coefficients were used to select the better coefficients by different optimal weighted sum of intensities algorithm for fusion. Experimental results show that compared with PWF de-speckling algorithm, the proposed algorithm can get better visual effect and achieve an excellent balance between suppresses speckle effectively and preserves image details, and the significant information of original image like textures and contour details is well maintained.