基于NSCT的红外偏振与光强图像的融合研究

针对融合规则的选择,提出了一种基于非采样Contourlet变换的红外偏振与光强的融合方法。该算法采用NSCT对源图像进行多尺度、多方向分解,然后对低频子带系数和高频子带系数分别采用局部能量和区域目标特征的选择,最终通过逆变换得到融合图像。实验结果表明：与加权融合和绝对值取大的融合规则相比,局部标准偏差、局部粗糙度、对比度、分别提高3.42%、12.7%、9.67%。

Fusion of Infrared Polarization and Intensity Images Based on NSCT

According to the choice of fusion rules, a fusion algorithm based on non-subsampled Contourlet transform(NSCT)is proposed for infrared polarization and light intensity image fusion. Firstly, the NSCT is used to perform the multi-scale and multi-direction decomposition of the source images. Then the low frequency sub-band coefficients and high frequency sub-band coefficients of the fused images can be obtained by the fusion rules based on the local energy and regional characteristic of the target. The experimental results show that the local standard deviation increases by 3.42%, the local coarseness increases by 12.7% and the contrast increases by 9.67%, by comparing with the fusion rules of weighted average and maximum absolute value.