Sub-Micron Spatial Resolution in Far-Field Raman Imaging Using Positivity-Constrained Super-Resolution. Issue 8 (August 2019)

• Record Type: Journal Article
• Authors: Winterauer, Dominik J.; Funes-Hernando, Daniel; Duvail, Jean-Luc; Moussaoui, Saïd; Batten, Tim; Humbert, Bernard
• Is Part Of: Applied spectroscopy. Volume 73:Issue 8(2019)
• Page Start: 902
• Page End: 909
• Publication Date: 2019-08
• Subjects: Super-resolution -- digital image restoration -- Raman spectroscopy -- nanomaterials; Spectrum analysis -- Periodicals; 543.505
• DOI: 10.1177/0003702819832355
• Languages: English
• ISSNs: 0003-7028

Abstract

Raman microscopy is a valuable tool for detecting physical and chemical properties of a sample material. When probing nanomaterials or nanocomposites the spatial resolution of Raman microscopy is not always adequate as it is limited by the optical diffraction limit. Numerical post-processing with super-resolution algorithms provides a means to enhance resolution and can be straightforwardly applied. The aim of this work is to present interior point least squares (IPLS) as a powerful tool for super-resolution in Raman imaging through constrained optimization. IPLS's potential for super-resolution is illustrated on numerically generated test images. Its resolving power is demonstrated on Raman spectroscopic data of a polymer nanowire sample. Comparison to atomic force microscopy data of the same sample substantiates that the presented method is a promising technique for analyzing nanomaterial samples.