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多类目标样片BRDF三维统计建模及优化 被引量:2

3-D BRDF Statistical Modeling and Optimizing of Surfaces of Various Materials and Roughness
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摘要 在Torrence-Sparrow模型的基础上,修正和简化了五参数模型,对多类目标样片双站多角度双向反射分布函数(BRDF)测量数据进行了拟合,在二维情况下与五参数模型进行了比较,两者均与实验数据吻合,表明了五参数模型良好的适应性,能够对不同粗糙度,不同光学特性的材料进行拟合。优化过程采用遗传算法与退火算法相结合,具有把握全局和较快收敛速度的特点,对于问题的解决起到了关键作用。五参数模型是三维空间模型,通过对某些样片的多组多角度双站三维实验数据进行的拟合充分利用了三维空间信息,建立了BRDF空间分布图,进而获得粗糙表面的更多光散射信息。 A modified and simplified five-parameter model is presented based on Torrance-Sparrow model. Multi-angle bi-static data of surfaces of various materials and roughness are fitted using this model. The results of the five-parameter model are in good agreement with the experimental data, which is close to the results of the two-dimensional bi-directional reflectance distribution function (BRDF) models. The five-parameter model shows a good applicability to various surface roughness and different optical materi- als. Genetic algorithm and simulated annealing algorithm are used to optimise the parameters for the model. The five-parameter model can be used to construct a 3-D BRDF distribution based on the spatial experimental data, which may provide more information of light scattering from rough surfaces.
出处 《南京理工大学学报》 EI CAS CSCD 北大核心 2007年第4期518-522,532,共6页 Journal of Nanjing University of Science and Technology
基金 国家自然科学基金(60371020)
关键词 双向反射分布函数 光散射 粗糙表面 遗传算法 退火算法 优化 bi-directional reflectance distribution function (BRDF) light scattering, rough sur-face genetic algorism simulated annealing algorism optimization
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