Structured illumination microscopy image reconstruction algorithm

February 19, 2016 ยท Entered Twilight ยท ๐Ÿ› IEEE Journal of Selected Topics in Quantum Electronics

๐ŸŒ… TWILIGHT: Old Age
Predates the code-sharing era โ€” a pioneer of its time

"Last commit was 9.0 years ago (โ‰ฅ5 year threshold)"

Evidence collected by the PWNC Scanner

Repo contents: .gitattributes, .gitignore, OpenSIM manual.pdf, SIMbasic, SIMexpt, TIRFbasic, TIRFexpt

Authors Amit Lal, Chunyan Shan, Peng Xi arXiv ID 1602.06904 Category cs.CV: Computer Vision Citations 181 Venue IEEE Journal of Selected Topics in Quantum Electronics Repository https://github.com/LanMai/OpenSIM โญ 57 Last Checked 1 month ago
Abstract
Structured illumination microscopy (SIM) is a very important super-resolution microscopy technique, which provides high speed super-resolution with about two-fold spatial resolution enhancement. Several attempts aimed at improving the performance of SIM reconstruction algorithm have been reported. However, most of these highlight only one specific aspect of the SIM reconstruction -- such as the determination of the illumination pattern phase shift accurately -- whereas other key elements -- such as determination of modulation factor, estimation of object power spectrum, Wiener filtering frequency components with inclusion of object power spectrum information, translocating and the merging of the overlapping frequency components -- are usually glossed over superficially. In addition, most of the work reported lie scattered throughout the literature and a comprehensive review of the theoretical background is found lacking. The purpose of the present work is two-fold: 1) to collect the essential theoretical details of SIM algorithm at one place, thereby making them readily accessible to readers for the first time; and 2) to provide an open source SIM reconstruction code (named OpenSIM), which enables users to interactively vary the code parameters and study it's effect on reconstructed SIM image.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Computer Vision