Adaptive total variation based autofocusing strategy in ptychography. (November 2022)

• Record Type: Journal Article
• Authors: Ruan, Tianhao; Lv, Wenjin; Tao, Ye; Zhang, Junhao; Yan, Xutong; Yang, Dongyu; Shi, Yishi
• Is Part Of: Optics and lasers in engineering. Volume 158(2022)
• Publication Date: 2022-11
• Subjects: Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2022.107136
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlights: We proposed an adaptive Lp-norm based total variation (TV) model and apply its variogram to design an image quality assessment metric. The proposed adaptive algorithm achieves high accuracy, efficiency and stability, it can alleviate the rigorous requirement of a prior parameter settings. The algorithm is applicable to various specimens. The setting range of the initial setting of specimen-detector distance is widely expanded, which means the method can work efficiently and stably with poorly estimated distance. Our searching method is practical and time-saving for ptychography. Combined with the Adam optimizer, our algorithm enables stabler and faster convergence. Abstract: In ptychography, the axial diffraction distance between specimen and detector is extremely important since the precision of this a prior parameter can strongly affect the quality of reconstruction. However, in experiments, applying a simple evaluation model for image quality assessment (IQA) will result in low accuracy with various specimens in the autofocusing methods. In this paper, we propose an autofocusing strategy with adaptive Lp-norm based total variation (TV) model, which achieves high accuracy of the convergence. It has been verified in optical experiments that our method is applicable to various types of specimens. Besides, the method can work efficiently and stably with poorly estimated specimen-detector distance.