The Structural Similarity (SSIM) Index is a very widely used image/video quality model that continues to play an important role in the perceptual evaluation of compression algorithms, encoding recipes and numerous other image/video processing algorithms. Several public implementations of the SSIM and Multiscale-SSIM (MS-SSIM) algorithms have been developed, which differ in efficiency and performance. This "bendable ruler" makes the process of quality assessment of encoding algorithms unreliable. To address this situation, we studied and compared the functions and performances of popular and widely used implementations of SSIM, and we also considered a variety of design choices. Based on our studies and experiments, we have arrived at a collection of recommendations on how to use SSIM most effectively, including ways to reduce its computational burden.
翻译:结构相似性指数(SSIM)是一个非常广泛使用的图像/视频质量模型,在对压缩算法、编码配方和许多其他图像/视频处理算法进行感知性评估方面继续发挥重要作用。已经开发了一些公众应用SSSIM和多尺度SSIM算法(MS-SSIM)的系统,这些算法在效率和性能上各不相同。这个“可移植标尺”使得编码算法的质量评估过程不可靠。为了应对这种情况,我们研究并比较了普遍和广泛使用的实施SSSIM的功能和表现,我们还考虑了各种设计选择。根据我们的研究和实验,我们收集了关于如何最有效地使用SSSIM的建议,包括减少计算负担的方法。