multissim
Multiscale structural similarity (MS-SSIM) index for image quality
Syntax
Description
score = multissim(I,Iref)score, for image I, using
Iref as the reference image.
The structural similarity (SSIM) index measures perceived quality by quantifying the
SSIM between an image and a reference image (see ssim). This function calculates the MS-SSIM index by combining the SSIM index
of several versions of the image at various scales. The MS-SSIM index can be more robust
when compared to the SSIM index with regard to variations in viewing conditions.
[
also returns the local MS-SSIM index value for each pixel in each scaled version of
score,qualitymaps] = multissim(I,Iref)I. The qualitymap output is a cell array
containing maps for each of the scaled versions of I. Each quality map
is the same size as the corresponding scaled version of I.
[
specifies options, using one or more name-value arguments. These options control aspects of
the computation. For example, use the score,qualitymaps] = multissim(I,Iref,Name,Value)'NumScales' argument to specify the
number of scaled versions.
Examples
Calculate MS-SSIM
Load an image into the workspace.
Iref = imread('pout.tif');Create a noisy version of the image for comparison purposes.
I = imnoise(Iref,'salt & pepper',0.05);Display the original image and noisy image.
figure;
montage({Iref,I}); 
Calculate the MS-SSIM index that measures the quality of the input image compared to the reference image.
score = multissim(I,Iref)
score = single
0.6732
Calculate MS-SSIM and Get Local MS-SSIM Maps
Load an image into the workspace.
Iref = imread('pout.tif');
I = Iref;Add noise to a localized part of the image.
I(1:100,1:100) = imnoise(Iref(1:100,1:100),'salt & pepper',0.05);Display the original image and the noisy image.
figure;
montage({Iref,I});
Calculate the local MS-SSIM index maps for the noisy image, qualitymaps, using the original image as the reference. The return value, qualitymaps, is a cell array containing a quality map for each of the scaled versions of the image. Each map is the same size as the corresponding scaled version of the image.
[~, qualitymaps] = multissim(I,Iref);
figure
montage(qualitymaps,'Size',[1 5])
Calculate MS-SSIM Specifying Scale Weights
Load an image into the workspace.
Iref = imread('pout.tif');Create a noisy version of the image for comparison purposes.
I = imnoise(Iref,'salt & pepper',0.05);Display the original image and the noisy version of the image.
figure;
montage({Iref,I});
Calculate the MS-SSIM index for the noisy image, using the original image as the reference. Specify how much to weigh the local MS-SSIM index calculations for each scaled image, using the 'ScaleWeights' argument. The example uses the weight values defined in the article by Wang, Simoncelli, and Bovik.
score = multissim(I,Iref,'ScaleWeights',[0.0448,0.2856,0.3001,0.2363,0.1333])score = single
0.6773
Calculate MS-SSIM Index Specifying Standard Deviation
Load an image into the workspace.
Iref = imread('pout.tif');Create a noisy version of the image for quality measurement comparison purposes.
I = imnoise(Iref,'salt & pepper',0.05);Display the original image and the noisy image.
figure; montage({Iref,I});
Calculate the MS-SSIM index for the noisy image, using the original image as the reference. Specify a standard deviation value.
score = multissim(I,Iref,'Sigma',1)score = single
0.6726
Input Arguments
Output Arguments
Algorithms
The multissim function uses double-precision arithmetic for input
images of class double. All other types of input images use
single-precision arithmetic.
References
[1] Wang, Z., Simoncelli, E.P., Bovik, A.C. Multiscale Structural Similarity for Image Quality Assessment. In: The Thirty-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 1398–1402. Pacific Grove, CA, USA: IEEE, 2003. https://doi.org/10.1109/ACSSC.2003.1292216.