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Normalization of fringe patterns using the bidimensional empirical mode decomposition and the Hilbert transform

机译:使用二维经验模式分解和希尔伯特变换对条纹图案进行归一化

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摘要

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.
机译:我们评估一种数据驱动技术来执行条纹图案的偏置抑制和调制归一化。所提出的技术使用二维经验模式分解方法来分解一组固有频率模式中的条纹图案,并进行局部希尔伯特变换来表征模式的局部幅度以执行归一化。使用计算机模拟的不同条纹密度的条纹图案和具有高局部变化调制的照明缺陷来测试该技术的性能,并讨论其优点和局限性。最后,还说明了规范化方法在处理实际数据中的性能。

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