In MATLAB
Change the code of image reading and run Score.m. The input images should be RGB with the type int.
These four evaluation metrics are widely used in multi-focus image fusion.
The related papers are as follows:
[1]Hossny, M., Nahavandi, S., & Creighton, D. (2008). Comments on'Information measure for performance of image fusion'. Electronics letters, 44(18), 1066-1067. http://dro.deakin.edu.au/eserv/DU:30017835/hossny-commentsoninformation-2008.pdf
[2]Xydeas, C. A., & Petrovic, V. (2000). Objective image fusion performance measure. Electronics letters, 36(4), 308-309. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.332.7913&rep=rep1&type=pdf
[3]Yang, C., Zhang, J. Q., Wang, X. R., & Liu, X. (2008). A novel similarity based quality metric for image fusion. Information Fusion, 9(2), 156-160. https://www.sciencedirect.com/science/article/abs/pii/S1566253506000704
[4]Chen, Y., & Blum, R. S. (2009). A new automated quality assessment algorithm for image fusion. Image and vision computing, 27(10), 1421-1432. https://www.sciencedirect.com/science/article/pii/S026288560700220X
We also include Lytro dataset here, if it is used in your research, you might have to include the original paper. http://www.irisa.fr/temics/demos/lightField/index.html