Aiming at the problem that the polarization image fusion process does not make good use of the polarization imaging characteristics, we propose a polarization image fusion method based on polarization saliency. On the one hand, we propose a new definition of physical property characterization based on polarization properties:polarization saliency. We construct it from three perspectives: image difference, position, and contrast. On the other hand, we propose a polarization saliency based fusion network (PSGGAN). The information decision block is constructed to enhance the polarization salient information and texture detail information of the source image. The loss function based on polarization saliency is designed to regulate the pixel distribution constraints and the degree of polarization information preservation. Qualitative and quantitative experiments demonstrate the superiority of our PSGGAN over state-of-the-art methods in terms of visual effects and quantitative metrics.

中文翻译：

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基于偏振显着性的生成对抗网络偏振图像融合方法

针对偏振图像融合过程没有充分利用偏振成像特性的问题，提出一种基于偏振显着性的偏振图像融合方法。一方面，我们提出了基于偏振特性的物理特性表征的新定义：偏振显着性。我们从三个角度构建它：图像差异、位置和对比度。另一方面，我们提出了一种基于极化显着性的融合网络（PSGGAN）。构造信息决策块以增强源图像的偏振显着信息和纹理细节信息。设计基于偏振显着性的损失函数来调节像素分布约束和偏振信息保存程度。定性和定量实验证明了我们的 PSGGAN 在视觉效果和定量指标方面优于最先进的方法。