Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
MI: Fachverband Mikrosonden
MI 7: Poster: Microanalysis and Microscopy
MI 7.4: Poster
Mittwoch, 22. März 2017, 18:00–20:00, P4
Improving Holographic Image Reconstruction by Statistical Multi-resolution Estimation — •Stephan Kramer1 and Johannes Hagemann2 — 1Fraunhofer ITWM, Fraunhofer-Platz 1, 67663 Kaiserslautern — 2Institut für Röntgenphysik, Universität Göttingen, Friedrich-Hund-Platz 1, 37077 Göttingen
We study the applicability of statistical multiresolution estimation (SMRE) to the problem of phase reconstruction in X-ray near-field holography. X-ray imaging experiments essentially yield near-field holograms. Despite their high quality they still contain noise and blur due to imaging errors. To get the final image of the object of interest its phases have to be retrieved from the measured hologram. To improve the input to this phase reconstruction we deconvolve and denoise a hologram either with our implementation of SMRE [1,2] or with Matlab's Richardson-Lucy (RL) algorithm, where the latter serves as reference. To assess the quality we study the number of fringes restored and the sharpness of edges after the phase reconstruction. Our results show that, in contrast to RL, our SMRE method is able to improve the holograms and thus the phase reconstruction.
[1] Kramer, S.C., Hagemann, J., Künneke L. and Lebert, J., 2016. SIAM Journal on Scientific Computing, 38(5), pp.C533-C559.
[2] Kramer, S.C. and Hagemann, J., 2015. ACM TOPC, 1(2), p.15.