Since specular reflection often exists in the real captured images and causes deviation between the recorded color and intrinsic color, specular reflection separation can bring advantages to multiple applications that require consistent object surface appearance. However, due to the color of an object is significantly influenced by the color of the illumination, the existing researches still suffer from the near-duplicate challenge, that is, the separation becomes unstable when the illumination color is close to the surface color. In this paper, we derive a polarization guided model to incorporate the polarization information into a designed iteration optimization separation strategy to separate the specular reflection. Based on the analysis of polarization, we propose a polarization guided model to generate a polarization chromaticity image, which is able to reveal the geometrical profile of the input image in complex scenarios, e.g. , diversity of illumination. The polarization chromaticity image can accurately cluster the pixels with similar diffuse color. We further use the specular separation of all these clusters as an implicit prior to ensure that the diffuse component will not be mistakenly separated as the specular component. With the polarization guided model, we reformulate the specular reflection separation into a unified optimization function which can be solved by the ADMM strategy. The specular reflection will be detected and separated jointly by RGB and polarimetric information. Both qualitative and quantitative experimental results have shown that our method can faithfully separate the specular reflection, especially in some challenging scenarios.

中文翻译：

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偏振引导镜面反射分离

由于实际拍摄的图像中经常存在镜面反射，导致记录的颜色与固有颜色之间存在偏差，因此镜面反射分离可以为需要一致物体表面外观的多种应用带来优势。然而，由于物体的颜色受光照颜色的影响很大，现有的研究仍然面临近乎重复的挑战，即当光照颜色接近表面颜色时，分离变得不稳定。在本文中，我们推导出偏振引导模型，将偏振信息纳入设计的迭代优化分离策略中，以分离镜面反射。基于对偏振的分析，我们提出了一种偏振引导模型来生成偏振色度图像，例如，照明的多样性。偏振色度图像可以准确地聚类具有相似漫反射颜色的像素。我们进一步使用所有这些簇的镜面反射分离作为隐式先验，以确保漫反射分量不会被错误地分离为镜面反射分量。使用偏振引导模型，我们将镜面反射分离重新表示为统一的优化函数，该函数可以通过 ADMM 策略解决。镜面反射将被 RGB 和偏振信息联合检测和分离。定性和定量的实验结果都表明，我们的方法可以忠实地分离镜面反射，尤其是在一些具有挑战性的场景中。