Schikora, Christoph MarkusPlack, MarkusBornemann, RainerBolívar, Peter HaringKolb, AndreasHeer, Jeffrey and Ropinski, Timo and van Wijk, Jarke2017-06-122017-06-1220171467-8659https://doi.org/10.1111/cgf.13183https://diglib.eg.org:443/handle/10.1111/cgf131832D Confocal Raman Microscopy (CRM) data consist of high dimensional per-pixel spectral data of 1000 bands and allows for complex spectral and spatial-spectral analysis tasks, i.e., in material discrimination, material thickness, and spatial material distributions. Currently, simple integral methods are commonly applied as visual analysis solutions to CRM data which exhibit restricted discrimination power in various regards. In this paper we present a novel approach for the visual analysis of 2D multispectral CRM data using multi-variate visualization techniques. Due to the large amount of data and the demand of an explorative approach without a-priori restriction, our system allows for arbitrary interactive (de)selection of varaibles w/o limitation and an unrestricted online definition/construction of new, combined properties. Our approach integrates CRM specific quantitative measures and handles material-related features for mixed materials in a quantitative manner. Technically, we realize the online definition/construction of new, combined properties as semi-automatic, cascaded, 1D and 2D multidimensional transfer functions (MD-TFs). By interactively incorporating new (raw or derived) properties, the dimensionality of the MD-TF space grows during the exploration procedure and is virtually unlimited. The final visualization is achieved by an enhanced color mixing step which improves saturation and contrast.I.3.3 [Computer Graphics]Display algorithmI.4.10 [Image Processing and Computer Vision]MultidimensionalI.5.3 [Pattern Recognition]Algorithms10.1111/cgf.13183239-249