论文标题
DSSIM：浮点数据的结构相似性索引
DSSIM: a structural similarity index for floating-point data
论文作者
论文摘要
在与大型模型仿真代码与浮点输出数据相互作用方面，数据可视化是关键组件。实际上，在模拟数据上进行分析的后处理分析工作流程通常会从原始数据中产生大量图像，然后将其中许多图像相互比较或指定的参考图像。在此图像启动方案中，图像质量评估（IQA）措施非常有用，结构相似性指数（SSIM）仍然是一个流行的选择。但是，生成大量图像的成本可能很昂贵，并且特定于图（但独立于数据）的选择可能会影响SSIM值。一个自然的问题是，我们是否可以将SSIM直接应用于浮点模拟数据，并获得指示数据中的差异是否可能影响视觉评估，从而有效地绕开了从数据中创建一组特定图像集。为此，我们提出了可以直接应用于浮点数据的流行SSIM的替代方法，我们称之为数据SSIM（DSSIM）。尽管我们在评估流行气候模型的大量仿真数据上评估差异的背景下证明了DSSIM的有用性，但DSSIM可能对许多其他涉及模拟或图像数据的应用程序有用。
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. A natural question is whether we can apply the SSIM directly to the floating-point simulation data and obtain an indication of whether differences in the data are likely to impact a visual assessment, effectively bypassing the creation of a specific set of images from the data. To this end, we propose an alternative to the popular SSIM that can be applied directly to the floating point data, which we refer to as the Data SSIM (DSSIM). While we demonstrate the usefulness of the DSSIM in the context of evaluating differences due to lossy compression on large volumes of simulation data from a popular climate model, the DSSIM may prove useful for many other applications involving simulation or image data.
