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Improvement of the quality of the interferogram based on the Gaussian process regression

机译:基于高斯进程回归的干涉图的提高

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Interferometric techniques are very important in the metrology field, while the quality of the interferogram will directly affect the retrieval phase of the tested object. This paper presents a method to improve the quality of the interferogram including restoration of noise aliasing and moire distortion by using the Gaussian Process Regression (GPR). Through choosing a suitable covariance function to describe the relationship between points and points in the fringe pattern, we build a Gaussian process regression model of interferogram, denoise the interferogram and improve the resolution at the same time. The treated interferogram can predict and compensate the part of the fringe distortion and enlarge the depth range of the interferometric measurement. Besides, with the resolution elevated of the hologram, a wider spectrum range can be obtained. In order to verify the possibility of this method, several simulations have been done, which showed a good performance in the enhancement of the quality of interferogram.
机译:干涉测量技术在计量场中非常重要,而干涉图的质量将直接影响测试对象的检索阶段。本文提出了一种提高干扰图的质量的方法,包括通过使用高斯过程回归(GPR)来恢复噪声混叠和莫尔畸变。通过选择合适的协方差函数来描述条纹图案中的点和点之间的关系,我们构建了干扰图的高斯过程回归模型,同时表达了干涉图并提高了分辨率。经处理的干涉图可以预测和补偿条纹变形的一部分,并扩大干涉测量的深度范围。此外,通过全息图升高的分辨率,可以获得更广泛的频谱范围。为了验证这种方法的可能性,已经完成了几种模拟,这在增强干扰图的增强方面表现出良好的性能。

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