DSSIM: a structural similarity index for floating-point data

Understand

Data visualization is a critical component in terms of interacting with floating-point output data from large model simulation codes.

• Indeed, postprocessing analysis workflows on simulation data often generate a large number of images from the raw data, many of which are then compared to each other or to specified reference images.
• In this image-comparison scenario, image quality assessment (IQA) measures are quite useful, and the Structural Similarity Index (SSIM) continues to be a popular choice.
• However, generating large numbers of images can be costly, and plot-specific (but data independent) choices can affect the SSIM value.