基于Kubelka-Munk理论的涂层表面多参量偏振双向反射分布函数模型

Multiple-Component Polarized Bidirectional Reflectance Distribution Function Model for Painted Surfaces Based on Kubelka-Munk Theory

为了表征涂层的表面散射偏振特性,基于Kubelka-Munk理论,综合考虑表面散射和体散射,建立了一种多参量偏振双向反射分布函数(BRDF)模型;该模型通过引入镜向系数来表征表面散射的贡献程度,以改进传统的偏振BRDF模型,使得含5个参量(复折射率的实部和虚部、表面粗糙度、相对漫反射率系数、镜向系数)的新偏振BRDF模型更符合实际的涂层表面散射偏振特性;通过开展户外实验获得黑漆和绿漆涂层表面在不同观测几何时的偏振度,利用遗传算法从实测数据中反演关键参量。结果表明:对于不同的涂层表面,该多参量偏振BRDF模型的仿真结果与实测数据均能较好地吻合,引入镜向系数能够提高模型的准确性,可为涂层目标偏振特征的提取和有效识别提供依据。

To represent scattering polarization properties of painted surfaces,a multiple-component polarized bidirectional reflectance distribution function（BRDF）model is established on the basis of the Kubelka-Munk（KM）theory with the consideration of surface scattering and volume scattering.The model introduces the mirror parameter to characterize surface scattering contributions,and improves the traditional polarized BRDF model to make the new polarized BRDF model containing five parameters（real and imaginary parts of complex refractive index,surface roughness,relative diffuse reflectance coefficient,and mirror parameter）more consistent with the actual scattering polarization of painted surfaces.The degrees of polarization of black and green painted surfaces at different observation geometries are obtained by the outdoor experiment.The genetic algorithm is used to obtain key parameters based on measured data.The results show that the simulated results coincide with the experimental data for different painted surfaces,and the accuracy is improved by the introduction of mirror parameter.This work can be used as a basis for the extraction and effective identification of painted target polarization feature.