Main Content

Multiscale structural similarity (MS-SSIM) index for volume quality

calculates the multiscale structural similarity (MS-SSIM) index, `score`

= multissim3(`V`

,`Vref`

)`score`

,
for volume `V`

, using `Vref`

as the reference
volume.

The 3-D MS-SSIM operation is defined for grayscale volumes. For inputs with more than
three dimensions, `multissim3`

treats each element of higher dimensions
as separate 3-D grayscale volumes. `multissim3`

treats 2-D RGB images as
3-D grayscale volumes. To calculate the MS-SSIM of color channels in an RGB image, use the
`multissim`

function.

`[`

also returns the local MS-SSIM index value for each voxel in `score`

,`qualityMaps`

] = multissim3(`V`

,`Vref`

)`V`

, and
each of the scaled versions of `V`

. The `qualityMaps`

output is a cell array containing maps for each of the scaled versions of
`V`

, with each quality map the same size as the corresponding scaled
version.

`[___] = multissim3(`

controls aspects of the computation using one or more name-value arguments. For example,
specify the number of scales using the `V`

,`Vref`

,`Name,Value`

)`'NumScales'`

argument.

The structural similarity (SSIM) index measures perceived quality by quantifying the
structural similarity between a volume and a reference volume (see `ssim`

). The `multissim3`

function calculates the MS-SSIM by
combining the SSIM index of several versions of the volume at various scales. The MS-SSIM
index can be more robust when compared to the SSIM index with regard to variations in viewing
conditions.

The `multissim3`

function uses double-precision arithmetic for input
volumes of class `double`

. All other types of input volumes use
single-precision arithmetic.

[1]