Bernini María B, Federico Alejandro, Kaufmann Guillermo H
Instituto de Física Rosario, Boulevard 27 de Febrero 210 bis, S2000EZP Rosario, Argentina.
Appl Opt. 2009 Dec 20;48(36):6862-9. doi: 10.1364/AO.48.006862.
We evaluate a data-driven technique to perform bias suppression and modulation normalization of fringe patterns. The proposed technique uses a bidimensional empirical mode decomposition method to decompose a fringe pattern in a set of intrinsic frequency modes and the partial Hilbert transform to characterize the local amplitude of the modes in order to perform the normalization. The performance of the technique is tested using computer simulated fringe patterns of different fringe densities and illumination defects with high local variations of the modulation, and its advantages and limitations are discussed. Finally, the performance of the normalization approach in processing real data is also illustrated.
我们评估一种数据驱动技术，以对条纹图案进行偏差抑制和调制归一化。所提出的技术使用二维经验模态分解方法将条纹图案分解为一组固有频率模式，并使用部分希尔伯特变换来表征这些模式的局部幅度，以便进行归一化。使用具有不同条纹密度和照明缺陷的计算机模拟条纹图案对该技术的性能进行了测试，这些条纹图案具有高度局部变化的调制，并且讨论了其优点和局限性。最后，还展示了归一化方法在处理实际数据时的性能。
