PRwSC - A Toolbox for Phase Retrieval with Sparsity Constraints
PRwSC is a toolbox for two-dimensional phase retrieval problems from simulated
data to experimental data with a focus on sparsity constraints using shearlets.
There is a Matlab version as well as a Python variant (pyPRwSC).
The toolbox needs the following Python packages in order to work properly:
pyPRwSC has been developed and tested with Python 3.6 using the Anaconda package
on Linux (Ubuntu 16.04.2 LTS), Windows 10 and Mac OS X (10.11-10.12).
A Matlab variant is also available (PRwSC, see download section). PRwSC needs
ShearLab3D to function properly. See the installation instruction included in
the ZIP archive for further information.
A schematic drawing of the structure of the toolbox can be seen
here (Matlab version).
Python: pyPRwSC (Version 1.0)
Matlab: PRwSC (Version 1.0)
You can simply download, unzip and use pyPRwSC. Depending on your specific Python
development environment, you may want to add the pyPRwSC folder to your Python
environment (Python Path). The dependencies can be installed using pip. If you use
Anaconda, they are already installed. A working copy of pyShearLab is also included
in the download.
In order to use pyPRwSC you need to import it as a module, see simulationComparison.py
as an example. This example of the reconstruction of a phase object provides all neccessary
steps to understand how to use the toolbox. A more detailed description of the Matlab
version of the toolbox is given in the documentation for the Matlab
pyPRwSC was written by Stefan Loock who acknowledges funding by the
SFB 755 Nanoscale Photonic Imaging.
Some functions like MagProj and calculateKLDistance were originally written for Matlab
by Russell Luke and are part
of the ProxToolbox.
The implementation of the Fresnel transform is based on prop_fresnel.m written by
For details see his PhD thesis:
- M. Krenkel. Cone-beam x-ray phase-contrast tomography for the observation of single cells in whole organs.
PhD thesis, Georg-August-Universität Göttingen, 2015.
The synthetic image of a cell is from Klaus Giewekemeyer, for information please see
- K. Giewekemeyer. A study on new approaches in coherent x-ray microscopy of biological
specimens. PhD thesis, Georg-August-Universität Göttingen, 2011.
- K. Giewekemeyer, S. P. Krüger, S. Kalbfleisch, M. Bartels, C. Beta, and T. Salditt.
X-ray propagation microscopy of biological cells using waveguides as a quasi point source.
Physical Review A, 83(2): 023804, 2011.