Rigorous simulation of speckle fields caused by large area rough surfaces using fast algorithms based on higher order boundary element methods

使用基于高阶边界元方法的快速算法对大面积粗糙表面引起的散斑场进行严格模拟

• 批准号: 375876714
• 负责人: Professor Dr. Wolfgang Osten
• 金额: --
• 依托单位: Institut für Technische Optik (ITO)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/375876714?language=en
• 关键词: Rigorous; simulation; speckle; fields; caused

Light scattering from rough surfaces are involved in wide-ranging practical applications such as remote sensing, optical metrology for surface inspection, cancer detection in medical imaging, or vibration and strain measurements in solid mechanics. Speckle phenomena can be observed in almost any optical coherent imaging and measurement. Profound information of the surface under inspection can be retrieved via analyzing the speckle fields. Rigorous calculation is therefore indispensable for understanding the speckle properties and for evaluating the properties of the involved surfaces and structures. Although rigorous simulation has been widely studied for a long time, many questions are still open due to the complexity of the problem and the formidable computational challenge. These include how the type of meshing element influences the results, how fine the surface should be meshed, and what a physical size is needed for surfaces with different roughness and materials. In further, inverse approaches to derive surface parameters from measured scattered field are strongly desired, but have not yet been well studied due to the absence of fast rigorous simulators. The objective of this project is to improve the performance of a speckle simulator (calculation speed, area of interest and surface properties), which we have developed using higher order boundary element method and surface integral equations. On this basis, we will in this project implement a fast multipole method (FMM) and its multilevel version, namely, a multilevel fast multipole method (MLFMM). With these algorithms, the computation and memory cost will be reduced from O(NxN) to O(Nlog(N)). Experimentally, we will fabricate surfaces with different roughness of different materials and will measure the BRDF and speckle fields using a setup to be built. Through comparing the simulated results with the measured, we will validate our implementation and build benchmarks for rough surface simulations. In particular, we will provide specklegrams as training examples for a machine learning process.

粗糙表面的光散射涉及广泛的实际应用，如遥感、表面检测的光学计量、医学成像中的癌症检测或固体力学中的振动和应变测量。在几乎任何光学相干成像和测量中都可以观察到散斑现象。通过对散斑场的分析，可以获取被检表面的深层信息。因此，严格的计算对于理解散斑特性和评估所涉及的表面和结构的特性是必不可少的。虽然严格模拟已经被广泛研究了很长时间，但由于问题的复杂性和巨大的计算挑战，许多问题仍未解决。这些包括网格元素的类型如何影响结果，表面应该网格化的精细程度，以及具有不同粗糙度和材料的表面需要多大的物理尺寸。此外，从测量的散射场中获得表面参数的逆方法是迫切需要的，但由于缺乏快速严格的模拟器，尚未得到很好的研究。该项目的目标是提高散斑模拟器的性能（计算速度，感兴趣的区域和表面性质），我们已经开发了使用高阶边界元方法和表面积分方程。在此基础上，我们将在本项目中实现快速多极子方法（FMM）及其多级版本，即多级快速多极子方法（MLFMM）。使用这些算法，计算和内存开销将从O（NxN）减少到O（Nlog(N)）。在实验中，我们将制造不同材料的不同粗糙度的表面，并将使用要构建的设置来测量BRDF和散斑场。通过将模拟结果与测量结果进行比较，我们将验证我们的实现并建立粗糙表面模拟的基准。特别地，我们将提供散斑图作为机器学习过程的训练示例。