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Data visualization is a critical component in terms of interacting withfloating-point output data from large model simulation codes. Indeed,postprocessing analysis workflows on simulation data often generate a largenumber of images from the raw data, many of which are then compared to eachother or to specified reference images. In this image-comparison scenario,image quality assessment (IQA) measures are quite useful, and the StructuralSimilarity Index (SSIM) continues to be a popular choice. However, generatinglarge numbers of images can be costly, and plot-specific (but data independent)choices can affect the SSIM value. A natural question is whether we can applythe SSIM directly to the floating-point simulation data and obtain anindication of whether differences in the data are likely to impact a visualassessment, effectively bypassing the creation of a specific set of images fromthe data. To this end, we propose an alternative to the popular SSIM that canbe applied directly to the floating point data, which we refer to as the DataSSIM (DSSIM). While we demonstrate the usefulness of the DSSIM in the contextof evaluating differences due to lossy compression on large volumes ofsimulation data from a popular climate model, the DSSIM may prove useful formany other applications involving simulation or image data.

DSSIM: a structural similarity index for floating-point data