PtyLab.m/py/jl: a cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography
arXiv:2301.06595 · doi:10.1364/OE.485370
Abstract
Conventional (CP) and Fourier (FP) ptychography have emerged as versatile quantitative phase imaging techniques. While the main application cases for each technique are different, namely lens-less short wavelength imaging for CP and lens-based visible light imaging for FP, both methods share a common algorithmic ground. CP and FP have in part independently evolved to include experimentally robust forward models and inversion techniques. This separation has resulted in a plethora of algorithmic extensions, some of which have not crossed the boundary from one modality to the other. Here, we present an open source, cross-platform software, called PtyLab, enabling both CP and FP data analysis in a unified framework. With this framework, we aim to facilitate and accelerate cross-pollination between the two techniques. Moreover, the availability in Matlab, Python, and Julia will set a low barrier to enter each field.
References in corpus (9)
- scikit-image: Image processing in Python
- Wide-field, high-resolution Fourier ptychographic microscopy
- The Complex Gradient Operator and the CR-Calculus
- Spectrum multiplexing and coherent-state decomposition in Fourier ptychographic imaging
- PyNX: high performance computing toolkit for coherent X-ray imaging based on operators
- Using Automatic Differentiation as a General Framework for Ptychographic Reconstruction
- Field-portable quantitative lensless microscopy based on translated speckle illumination and sub-sampled ptychographic phase retrieval
- Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation
- Proximity Operators for Phase Retrieval