Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images. Issue 1 (7th October 2014)

• Record Type: Journal Article
• Authors: Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas; Østergaard, Jan; Larsen, Torben
• Is Part Of: Journal of open research software. Volume 2:Issue 1(2014)
• Publication Date: 2014-10-07
• Subjects: Atomic Force Microscopy -- Compressive Sensing -- Python -- Image Reconstruction -- Reproducible Research; Computer software -- Reusability -- Periodicals; Open source software -- Periodicals; 005
• DOI: 10.5334/jors.bk
• Languages: English
• ISSNs: 2049-9647

Abstract

Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research.