Structure Similarity Index

Note: The structural similarity index (SSIM) is only possible between two datasets of the same dimensions.

Features:

Calculates the SSIM score for 3D datasets after datacube processing using original datacube as the reference image. This metric quantifies image changes caused by processing such as data filtering. A value closer to 1 indicates higher similarity to the original image.

Steps:

1.       Open a file and perform one of the image processing algorithms. For example, remove Gaussian noise by selecting Filtering and Enhancement → 3D Gaussian filtering. 

2.     After the filter is applied and completed, select Filtering and Enhancement → Structure Similarity Index.

A new pop-up window SSIM Score will produce the calculated structural similarity index. A value closer to 1 indicates higher similarity and a value closer to 0 indicates low similarity.

References:

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