SFB755 Nanoscale Photonic Imaging
Subproject - A4 -
Data driven image selection for photonic counting data

Partner:

• Deutsche Forschungsgemeinschaft
• Institute for x-ray-physics (Prof. Dr. Tim Salditt)
• MPI für biophsikalische Chemie:
  • Department of NanoBiophotonics (Director: Prof. Dr. Stefan W. Hell)
  • Department of Theoretical and Computational Biophysics (Prof. Dr. Helmut Grubmüller)

Project Management:

• Prof. Dr. A. Munk, Göttingen

Staff:

• Dr. Jörn Dannemann

Description:

Image reconstruction methods based on Poisson data from nano-scale (fluorescence) microscopy are based on regularization techniques to deconvolve the observed data. They require a proper selection of tuning parameters such as the stopping iteration in Richardson-Lucy deconvolution. Its automatic, i.e. purely data driven, choice is a major challenge in image processing. We will develop methods for Poisson data, with stochastic multiresolution analysis as the primary tool.