Parameter retrieval methods in ptychography

TL;DR

This paper introduces a parameter retrieval method combining ptychography with prior object knowledge, applied to small particles and rectangles, analyzing noise effects and theoretical bounds to improve accuracy.

Contribution

It proposes a novel parameter retrieval approach that integrates prior knowledge with ptychography, validated through applications and noise analysis.

Findings

Computed Cramér-Rao bounds for different noise levels

Verified bounds with Monte Carlo simulations

Analyzed particle correlation in applications

Abstract

We present a parameter retrieval method which combines ptychography and additional prior knowledge about the object. The proposed method is applied to two applications: (1) parameter retrieval of small particles from Fourier ptychographic dark field measurements; (2) parameter retrieval of retangule with real-space ptychography. The influence of Poisson noise is discussed in the second part of the paper. The Cram\'{e}r Rao Lower Bound in both two applications is computed and Monte Carlo analysis is used to verify the calculated lower bound. With the computation results we report the lower bound for various noise levels and the correlation of particles in Application 1. For Application 2 the correlation of parameters of the rectangule is discussed.