基于神经网络的粗糙表面双向反射分布函数建模

分析粗糙表面双向反射分布函数的测量方法,提出一种使用人工神经网络技术建立目标表面材料双向反射分布函数模型的方法。给出测量样品多个入射角度下的BRDF随散射角变化的曲线，从中选取部分曲线输入到神经网络，使用贝叶斯正则化方法训练网络，最终获取双向反射分布函数和入射角、散射角的映射关系模型。使用网络模型计算参与训练和未参与训练的输入角度的散射分布曲线，与实验测量曲线进行比较，结果表明：建立的模型正确，具有应用价值。

Modeling of bidirectional reflectance distribution function for rough surface by artificial neural network

The measurement method of the bidirectional reflectance distribution function (BRDF) for a rough surface was analyzed. A method to establish the BRDF model of the target surface material by artificial neural network is proposed. The sample BRDF curves variating with the scatter angle under several incident angles are given, and some of the curves were selected and sent into the artificial neural network. The network was trained with the Bayesian regularizing method. The mapping relation model of BRDF with incident and scatter angles was obtained. The scattering distribution curves under the incident angles, which participated in or did not participate in the training, were calculated with the network model. It was compared with the measured curves, and the result shows that the model is correct and practical.