Robust phase retrieval algorithm for noisy diffraction patterns using normalized convolution

T. Leportier, M. Park, Y. Jhon
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引用次数: 2

Abstract

Phase retrieval is an iterative method that has been developed to recover the lost phase information in coherent diffraction imaging. The most widely used algorithm is the hybrid input-output (HIO) algorithm because of its ability to avoid local minimum. Unfortunately the presence of noise in the images acquired disturbs the convergence of the algorithm. A few solutions have been proposed in order to improve the quality of the recovered images but they unfortunately still suffer from oscillations even though they are less susceptible to noise than the traditional method. In this paper, we propose a robust method to reconstruct diffraction patterns which are corrupted by Poisson noise. Our method relies on the HIO algorithm, combined with a Gaussian filter to avoid the oscillation and with normalized convolution (NC) to improve the quality of the filtered images. We describe the principle of our approach and present the results of simulations which have been made to evaluate its performance and to draw a comparison with the others existing algorithms that have been developed so far.
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使用归一化卷积的噪声衍射图鲁棒相位恢复算法
相位恢复是一种用于恢复相干衍射成像中丢失的相位信息的迭代方法。其中应用最广泛的算法是混合输入输出算法(HIO),因为它具有避免局部最小值的能力。不幸的是,所获得的图像中噪声的存在干扰了算法的收敛性。为了提高恢复图像的质量,已经提出了一些解决方案,但不幸的是,它们仍然受到振荡的影响,尽管它们比传统方法更不易受噪声的影响。本文提出了一种鲁棒的方法来重建被泊松噪声破坏的衍射图样。我们的方法依赖于HIO算法,结合高斯滤波器来避免振荡,并结合归一化卷积(NC)来提高滤波后图像的质量。我们描述了我们的方法的原理,并提出了模拟结果,以评估其性能,并与迄今为止开发的其他现有算法进行比较。
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