论文标题
使用光谱初始化的加速ptychographic重建
Accelerating ptychographic reconstructions using spectral initializations
论文作者
论文摘要
PtyChography是一种无标记定量相成像的有希望的相检索技术。相位检索算法的最新进展见证了光谱方法的发展，以加速梯度下降算法。使用实验数据上的光谱初始化，我们首次报告了ptychographic重建的三倍，是标准梯度下降算法和提高对噪声的弹性的三倍。与基于梯度的算法相比，没有额外的计算成本来实现，光谱方法有可能在大规模迭代的Ptychographic算法中实现。
Ptychography is a promising phase retrieval technique for label-free quantitative phase imaging. Recent advances in phase retrieval algorithms witnessed the development of spectral methods, in order to accelerate gradient descent algorithms. Using spectral initializations on experimental data, for the first time we report three times faster ptychographic reconstructions than with a standard gradient descent algorithm and improved resilience to noise. Coming at no additional computational cost compared to gradient-descent-based algorithms, spectral methods have the potential to be implemented in large-scale iterative ptychographic algorithms.
