A Hitchhiker's Guide to Structural Similarity
This addresses the need for reliable quality assessment in image/video processing for researchers and engineers, but it is incremental as it builds on existing SSIM methods.
The paper tackled the problem of inconsistent implementations of the Structural Similarity (SSIM) Index affecting image/video quality assessment reliability, resulting in recommendations for effective use and computational reduction.
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.