## 2 Proposed Fusion Scheme
Figure 7: Multi-focus image of a _craft_ from various perspectives. Original Image: (**a**), Multi-focus Input Images: (**b**,**c**), and Proposed Fusion: (**d**). ### Comparison of Desk Image Fusion with the Literature

The desk, depicted in Figure 10, is used to evaluate the second multi-focus image. In Figure 10, the original image is depicted in (a). Images with a left focus and a right focus, respectively, are shown in Figure 10b,c. Left-side focus is referred to as a \"left focused image\", while the right-side focus is referred to as a \"right unfocused image\". A right-focused image has only its right side considered; the left side has not been considered. Following a successful strategy implementation, Figure 10d depicts the procedure for producing the entire in-focus image. The following parameters are computed to measure the effectiveness of the given technique: \(E(F)\), \(AG_{F}\), \(CC\), \(Q^{ABF}\), \(SSIM\), and \(Q_{E}\). The proposed strategy's performance is then compared to other approaches already published in the literature. The comparison's findings are displayed in Table 4 of the report. The best results of methods are highlighted in bold, and the literature [20] indicates that the proposed strategy is more effective than existing methods. ### Comparison of Book Image Fusion with the Literature

The book, depicted in Figure 11, is used to evaluate the third multi-focus image. In Figure 11, in (a), the original image is depicted. Images with left and right focus are shown \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**MIF-Methods** & \(Q_{E}\) & \(Q^{ABF}\) & **E(F)** & \(CC\) & \(AG_{F}\) & \(SSIM\) \\ \hline PA-DCPCNN & 0.8669 & 0.8958 & 7.346 & **0.9644** & **8.215** & 0.8693 \\ Proposed Method & **0.9284** & **0.9960** & **7.3534** & 0.9626 & 8.1919 & **0.9895** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The results and comparisons for desk image ([20]). Figure 10: Multi-focus image of a desk from various perspectives. Original Image: (**a**), Multi-focus Input Images: (**b,c**), and Proposed Fusion: (**d**). Figure 9: Multi-focus image of a clock from various perspectives. Original Image: (**a**), Multi-focus Input Images: (**b,c**), and Proposed Fusion: (**d**). in Figure 11b,c, respectively. The phrase \"left focused image\" describes an image whose left side is focused but not right. While the left of the image is out of focus, the right side is. The method's creation of the all-in-focus image is depicted in Figure 11d after it has been successfully applied. The following parameters are computed to assess the efficiency of the proposed methodology: \(E(F)\), \(AG_{F}\), \(SSIM\), \(CC\), \(Q^{ABF}\), and \(Q_{E}\). Finally, the effectiveness of the proposed strategy is contrasted with other approaches previously reported in the literature. Table 5 of the report includes the comparison results. The proposed method is more effective than most of the other methods according to the literature [20] and the best results of the methods are noted in bold. ### Comparison of Flower Image Fusion with the Literature

The flower in Figure 12 is used to evaluate the fourth multi-focus image. In Figure 12, the original image is depicted in (a). Images with a left focus and a right focus, respectively, are shown in Figure 12b,c. Left-side focus is referred to as a \"left focused image\", while the right-side focus is referred to as a \"right unfocused image\". An image that is right-focused but not left-focused is one that is dominated by the right. The approach is put into practice, and the result is the all-in-focus image, as seen in Figure 12d. To evaluate the performance of the proposed methodology, calculations are made for \(SSIM\), \(E(F)\), \(CC\), \(AG_{F}\), \(Q^{ABF}\), and \(Q_{E}\). The performance of the proposed strategy is then contrasted with that of other approaches previously reported in the literature. The comparison's findings are shown in Table 6 of the report.