基于Directionlets变换的偏振图像融合

Fusion of Polarization Image Based on Directionlets Transform

论文提出一种有效的基于Directionlets变换的偏振图像融合算法。首先采用多方向多尺度的Directionlets变换对多个偏振图像进行分解,对于分解后的低频系数采用加权平均融合算法;根据高频子图边缘分布差异,对于方向高频系数采用2维Teager能量的边缘检测算法以及区域方向对比度算法实现偏振图像的融合处理。实验结果表明,与传统算法相比,提出的算法在保留原始图像边缘和纹理信息的同时,可以有效地取得较好的融合视觉效果。

An efficient image fusion algorithm for polarization images based on Directionlets transform is proposed. Firstly, the several of polarization images are decomposed using Directionlets transform, which have multi-scale, multi-direction characteristics. Then, for the low-pass coefficients, the weighted averaging fusion rule is used. To select the better coefficients for the directional high-frequency ones, edge detection using two dimensional Teager energy and region directional contrast algorithm are used for fusion according to edge distribution differences in high frequency sub-band images. Experimental results show that compared with traditional algorithm, the proposed algorithm can get better visual effect and the significant information of original image like textures and contour details is well maintained.