Welcome to the GlobalBioIm Library webpage!¶
When being confronted with a new inverse problem, the common experience is that one has to reimplement (if not reinvent) the wheel (=forward model + optimization algorithm), which is very time consuming and also acts as a deterrent for engaging in new developments. This Matlab library GlobalBioIm aims at simplifying this process by decomposing the workflow onto smaller modules, including many reusable ones since several aspects such as regularization and the injection of prior knowledge are rather generic. It also capitalizes on the strong commonalities between the various image formation models that can be exploited to obtain fast, streamlined implementations.
This page contains detailled documentation of each function/class of the Library. The documentation is generated automatically from comments within M-files. It thus constitues the most up-to date documentation of the Library.
- M. Unser, E. Soubies, F. Soulez, M. McCann, L. Donati, GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems Proceedings of the OSA Imaging and Applied Optics Congress on Computational Optical Sensing and Imaging (COSI‘17), San Francisco CA, USA, June 26-29, 2017, paper no. CTu1B.