`skvideo.measure`.videobliinds_features¶

skvideo.measure.videobliinds_features(videoData)[source]¶

Computes Video Bliinds features. [1]

Since this is a referenceless quality algorithm, only 1 video is needed. This function provides the raw features used by the algorithm.

Parameters:

Parameters:	videoData : 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.
Returns:	features : ndarray, shape (46,) The individual features of the algorithm. The features are arranged as follows: features[:36] : spatial niqe vector averaged over the video, shape (36,) features[36] : niqe naturalness score, shape (1,) features[37:39] : DC measurements between frames, shape (2,) features[39:44] : Natural Video Statistics, shape (5,) features[44] : Motion coherence, shape (1,) features[45] : Global motion, shape (1,)

videoData : 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.

Returns:

features : ndarray, shape (46,)

The individual features of the algorithm. The features are arranged as follows:

features[:36] : spatial niqe vector averaged over the video, shape (36,)

features[36] : niqe naturalness score, shape (1,)

features[37:39] : DC measurements between frames, shape (2,)

features[39:44] : Natural Video Statistics, shape (5,)

features[44] : Motion coherence, shape (1,)

features[45] : Global motion, shape (1,)

References

[1]	Saad and A.C. Bovik, “Blind prediction of natural video quality” IEEE Transactions on Image Processing, December 2013.

skvideo.measure.videobliinds_features¶

`skvideo.measure`.videobliinds_features¶