Improved phase-attenuation duality method with space-frequency joint domain iterative regularization.

Abstract

A common problem of in-line phase contrast imaging systems based on laboratory source and detector is the negative effects of finite source size, limited spatial resolution, and system noise. These negative effects swamp the fine phase contrast fringes and impede the precise retrieval of phase maps. This study aims to develop a novel phase retrieval method to restore phase information that is lost due to an imperfect system. An improved phase-attenuation duality (PAD) method based on space-frequency joint domain iterative regularization (JDIR) is proposed to overcome the problems of the analytical PAD method and the spatial-domain iterative regularization (SDIR) based PAD method. These problems include noise robustness and optical transfer function compensation. The proposed method was compared with the two former PAD methods through computer simulations and experiments for validation. Results reveal that JDIR method outperforms the other two methods in terms of improving the visibility of structures in the retrieved phase maps. Among all the phase retrieval algorithms, the TV-norm-based JDIR method performed the best in considering the contrast and noise performance. This paper provides a new method to investigate quantitative phase-contrast imaging when considering the negative effects of an imperfect system.