Hajihashemi M Reza, Jiang Huabei
Department of Biomedical Engineering, University of Florida, Gainesville, Florida 32611, USA.
J Opt Soc Am A Opt Image Sci Vis. 2012 Jun 1;29(6):1124-31. doi: 10.1364/JOSAA.29.001124.
The Gaussian-random-sphere model is employed for morphological characterization of nonspherical, irregular particles using an inverse light scattering technique. The synthetic measurement data consist of reduced scattering spectra caused by an aggregate of irregular particles randomly oriented in turbid media and are generated using the discrete dipole approximation. The proposed method simultaneously retrieves the concentration and shape parameters of particles using the data collected at multiple wavelengths. The performance of the inverse algorithm is tested using noise-corrupted data, in which up to 50% noise may be added to the observed scattering spectra.
高斯随机球体模型用于通过逆光散射技术对非球形、不规则颗粒进行形态表征。合成测量数据由浑浊介质中随机取向的不规则颗粒聚集体引起的简化散射光谱组成，并使用离散偶极近似生成。所提出的方法利用在多个波长收集的数据同时反演颗粒的浓度和形状参数。使用噪声污染数据测试逆算法的性能，其中可向观测到的散射光谱添加高达50%的噪声。
