Machine Learning for Big Data Analysis

When the SD value is high, it indicates a fused image at high contrast:

$\text{SD}=\sqrt{\frac{1}{MN}{\displaystyle \sum _{i=0}^{M-1}{\displaystyle \sum _{j=0}^{N-1}{\left(I\left(i,j\right)-\overline{I}\right)}^2}}},\left(6.54\right)$

where I and Ī are respectively the fused and mean of the fused image whose size is M × N.

6.4.1.6Root-mean-square error

The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is used to measure the contrasts between qualities anticipated by a model or an estimator and the qualities actually observed. The RMSD represents the sample SD of the differences between observed values and predicted values. The individual differences are known as residuals, where the calculations are performed over the data sample that was used for estimation, ...