特集 結晶学と情報学の融合
コヒーレント回折イメージングにおけるスパース位相回復アルゴリズム
2020 年 62 巻 1 号 p. 10-16
詳細
2020 年 62 巻 1 号 p. 10-16
In this study, we propose a sparse phase retrieval algorithm （SpPRA）, which involves an iterative Fourier transform and sparse modeling （LASSO）, and demonstrated that it can retrieve the phase from diffraction data including noise and missing information. Considering the sparseness of the target sample as regularization enables preventing over-fitting the noise and estimating the diffraction data of the missing region.
