## 2 Proposed Fusion Scheme
Figure 20: Fusion results of the proposed method for the multi-focus image pairs shown in Figure 18.

### Test on a Remote Sensing Image Pair

In the remote sensing image experiment, we used one image pair from remote sensing image fusion trial to determine how well these methods generalize to other image fusion use cases. In Table 14, the fusion results for the \"Remote sensing\" image pairings are displayed, while in Figure 22, the corresponding findings for the \"Remote sensing\" image pairs are visualized. The parameters _SSIM_, _E_(_F_), _CC_, _AG_\({}_{F}\), _Q_\({}^{AB/F}\), and _Q_\({}_{E}\) are calculated to assess the effectiveness of the proposed methodology. Finally, we compare the proposed method to those already described in the literature. Table 14 presents the comparison results for the report. The best results of each methodology are highlighted in bold, supporting the conclusion that the proposed strategy is superior to the alternatives presented in the literature [20]. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**MIF-Methods** & _E_(_F_) & _CC_ & _AG_\({}_{F}\) & _SSIM_ & _Q_\({}_{E}\) & _Q_\({}^{AB/F}\) \\ \hline PA-DCPCNN & 7.195 & **0.5219** & **12.6765** & 0.6679 & 0.6085 & 0.8229 \\ Proposed Method & **7.2322** & 0.4575 & 12.6270 & **0.8009** & **0.7213** & **0.8988** \\ \hline \hline \end{tabular}
\end{table} 
Table 14: The results and comparisons for remote sensing image ([20]). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**MIF-Methods** & _Q_\({}_{E}\) & _AG_ & _Q_\({}^{0}\) & _EI_ & _Q_\({}^{AB/F}\) & _GM_ & _ID_ & _SD_ \\ \hline DTCWT—CSR & 0.7433 & 7.6828 & 0.8152 & 77.7976 & 0.7745 & 103.8605 & 9.7117 & 52.0522 \\ CVT—CSR & 0.712 & 7.6924 & 0.8051 & 77.8838 & 0.742 & 104.4969 & 9.732 & 52.1355 \\ NSCT—CSR & 0.7186 & 7.6807 & 0.8327 & 77.7429 & 0.7571 & 104.6126 & 9.7074 & 52.2404 \\ DWT—CSR & 0.6941 & 7.7793 & 0.8168 & **78.6239** & 0.736 & 104.4005 & **9.8798** & 52.323 \\ Proposed Method & **0.9234** & **12.6504** & **0.9202** & 67.7652 & **0.9891** & **104.1459** & 8.6857 & **52.9553** \\ \hline \hline \end{tabular}
\end{table} 
Table 12: The average objective evaluation of different techniques on multi-focus image pairs ([22]). Figure 21: Medical Image Pair: (**a**,**b**) are source images, (**c**) Final fused image. Figure 22: Multi-focus image of a remote sensing from various perspectives: (**a**) the original image, (**b**) the image with the left focus, (**c**) the image with the right focus, and (**d**) the image fused using the proposed method. ## 4 Qualitative Comparison

Quantitative comparison is performed with \(E(F)\), \(Q_{E}\), \(Q^{AB/F}\), \(SSIM\), \(CC\), \(AGF\)\(Q^{0}\), \(SD\), \(EI\), \(ID\), and \(GM\). The entropy \(E(F)\) measures a fused image's information content. When the entropy of the combined image is high, there is much information there. Figure 23 shows the value of this measure for several image fusion techniques. The average improvement of the proposed method concerning entropy is 0.39% with reference to PA-DCPCNN [20]. \(Q_{E}\) quantifies the edge-dependent fusion quality index of the fused image. A higher \(Q_{E}\) indicates a more effective fusion strategy. Figure 24 illustrates the significance of this statistic across several image fusion approaches. The average improvement of the proposed method concerning \(Q_{E}\) is 5.32% with reference to PA-DCPCNN [20]. The amount of edge information (\(Q^{AB/F}\)) carried by the fused image within the source images is calculated by total-fusion performance. A larger value of \(Q^{AB/F}\) is desired. Figure 25 illustrates this metric's value for several image fusion techniques. The average improvement of the proposed method concerning \(Q^{AB/F}\) is 8.56% with reference to PA-DCPCNN [20]. Figure 23: Performance evaluation of image-fusion techniques in reference to \(E(F)\). Figure 24: Performance evaluation of image-fusion techniques in reference to \(Q_{E}\).