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Analyzing closed-fringe images using two-dimensional Fan wavelets

机译:使用二维Fan小波分析闭合条纹图像

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摘要

In this paper, it will be shown how the use of two 2D Fan wavelets to analyze closed-fringe images can lead to a relatively fast and exceptionally noise-resistant algorithm capable of extracting not only local phase but also local frequency information. Our algorithm is up to 10 times faster than the current state-of-the-art in wavelet processing techniques and even up to 30 times faster than "windowed Fourier" transform programs, which achieve similar noise-resiliency figures. This improvement is mainly achieved by the use of Fan wavelets instead of Morlet wavelets, but a more efficient scale-space discretization strategy is also described, and three different alternatives are suggested capable of solving the phase sign-ambiguity problem in a quick and efficient manner. Finally, the application of the algorithm to real and numerically generated images shows that a precision of 1/30th of a fringe is achievable for noise levels going up to 1/5th of the input contrast. (C) 2015 Optical Society of America
机译:在本文中,将展示如何使用两个2D Fan小波分析闭合条纹图像如何导致相对快速且异常抗噪的算法,该算法不仅能够提取局部相位,而且能够提取局部频率信息。我们的算法比小波处理技术中的最新技术快10倍,甚至比“窗口傅立叶”变换程序快30倍,后者实现了类似的抗噪能力。这种改进主要是通过使用Fan小波而不是Morlet小波来实现的,但是还描述了一种更有效的比例空间离散化策略,并且提出了三种能够快速有效地解决相位符号模糊性问题的替代方法。 。最后,将该算法应用于真实和数字生成的图像表明,对于噪声水平达到输入对比度的1/5的情况,可以达到条纹的1/30的精度。 (C)2015年美国眼镜学会

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