structural_similarity(im1, im2, *, win_size=None, gradient=False, data_range=None, multichannel=False, gaussian_weights=False, full=False, **kwargs)
To match the implementation of Wang et. al. , set :None:None:`gaussian_weights` to True, :None:None:`sigma` to 1.5, and :None:None:`use_sample_covariance` to False.
This function was renamed from skimage.measure.compare_ssim
to skimage.metrics.structural_similarity
.
If True, normalize covariances by N-1 rather than, N where N is the number of pixels within the sliding window.
Algorithm parameter, K1 (small constant, see ).
Algorithm parameter, K2 (small constant, see ).
Standard deviation for the Gaussian when :None:None:`gaussian_weights` is True.
Images. Any dimensionality with same shape.
The side-length of the sliding window used in comparison. Must be an odd value. If :None:None:`gaussian_weights` is True, this is ignored and the window size will depend on :None:None:`sigma`.
If True, also return the gradient with respect to im2.
The data range of the input image (distance between minimum and maximum possible values). By default, this is estimated from the image data-type.
If True, treat the last dimension of the array as channels. Similarity calculations are done independently for each channel then averaged.
If True, each patch has its mean and variance spatially weighted by a normalized Gaussian kernel of width sigma=1.5.
If True, also return the full structural similarity image.
The mean structural similarity index over the image.
The gradient of the structural similarity between im1 and im2 . This is only returned if gradient
is set to True.
The full SSIM image. This is only returned if :None:None:`full` is set to True.
Compute the mean structural similarity index between two images.
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.measure._structural_similarity.compare_ssim
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