Hyperspectral imaging (also known as spectrum imaging) requires software for extracting the signatures present in every spectrum. However, commercial software available for spectrum analysis remains expensive, complicated, and often not transparent regarding the internal workings and approximations made. For user facilities, educational institutes, and other settings where multiple users on a single tool can be expected, the limited availability of software becomes the bottleneck to data analysis, user training, and throughput. The Cornell Spectrum Imager (CSI) was developed as a universal data analysis tool to be freely distributed, to run on all computers, and to minimize training. This is accomplished by using one simple interface for imaging, cathodoluminescence, Raman, Electron Energy Loss Spectroscopic (EELS), and EDX data analysis. This article demonstrates the CSI plugins for ImageJ by guiding you through the basic workflow for processing EELS maps.
Email your librarian or administrator to recommend adding this journal to your organisation's collection.