skvideo.measure.msssim¶

skvideo.measure.msssim(referenceVideoData, distortedVideoData, method='product')[source]¶

Computes Multiscale Structural Similarity (MS-SSIM) Index. [1]

Both video inputs are compared frame-by-frame to obtain T MS-SSIM measurements on the luminance channel.

Parameters:

referenceVideoData : ndarray Reference video, ndarray of dimension (T, M, N, C), (T, M, N), (M, N, C), or (M, N), where T is the number of frames, M is the height, N is width, and C is number of channels. Here C is only allowed to be 1. distortedVideoData : ndarray Distorted video, ndarray of dimension (T, M, N, C), (T, M, N), (M, N, C), or (M, N), where T is the number of frames, M is the height, N is width, and C is number of channels. Here C is only allowed to be 1. method : str Whether to use “product” (default) or to use “sum” for combing multiple scales into the single score.

Returns:

msssim_array : ndarray The MS-SSIM results, ndarray of dimension (T,), where T is the number of frames

References

[1]	Wang, E. P. Simoncelli and A. C. Bovik, “Multi-scale structural similarity for image quality assessment,” IEEE Asilomar Conference Signals, Systems and Computers, Nov. 2003.