# Research on Multi-Scale Fusion Method for Ancient Bronze Ware X-ray Images in NSST Domain
## 3 Results
### Quantitative Analysis
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **EN** & **AG** & **MI** & **Q\({}^{\text{AB/F}}\)** & **PSNR** & **VIF** \\ \hline LDR & 4.7363 & 8.5674 & 3.5116 & 0.7018 & 64.3992 & 0.8996 \\ \hline NMP & 4.9137 & 8.5399 & 3.3463 & 0.7194 & 65.9793 & 0.8846 \\ \hline F-PCNN & 4.3255 & 8.2711 & 2.7491 & 0.6833 & 66.0695 & 0.8524 \\ \hline LatLRR & 4.9931 & 7.1796 & 3.7994 & 0.6743 & 66.0584 & 0.8867 \\ \hline IVFusion & 4.6186 & 9.3566 & 2.2805 & 0.5029 & 57.9520 & 0.8154 \\ \hline PL-NST & 4.3971 & 8.3602 & 2.8599 & 0.6598 & 65.4397 & 0.9006 \\ \hline MMIF & 5.1362 & 8.2784 & 3.0218 & 0.6204 & 65.4217 & 0.8653 \\ \hline IFE & 4.5993 & 9.4596 & 4.2301 & 0.7283 & 62.6021 & 0.9222 \\ \hline Proposed method & 4.7987 & 10.0025 & 4.5218 & 0.7594 & 65.9081 & 0.9832 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The six evaluation results of the third set of bronze mirror fusion result graphs. the other hand, reflects the quality of the visual information obtained from the source image by the fusion resultant map, with larger values indicating that more of the original information is retained after fusion. PSNR reflects whether the image is distorted or not, and ideally, a larger value indicates better image quality. VIF is indeed an evaluation index that incorporates the quality of human visual perception and has a strong correlation with human judgment of visual quality. In the context of methodology concerning cultural relics protection, the specific nature of this work emphasizes the significance of subjective human eye judgment. Hence, the introduction of VIF allows for a comprehensive assessment of visual quality, aligning with the aim of effectively preserving cultural relics. The method employed in this study demonstrates the highest values in all four evaluation indexes, namely AG, MI, Q\({}^{\text{AB}\text{(F)}}\), and VIF. Notably, it excels particularly in the VIF index, suggesting that this method is adept at capturing more intricate details from the source image during the fusion process of X-ray images of bronze mirrors. As a result, the fused image exhibits a richer texture, aligning more closely with human visual perception. The method of this study is ranked at a medium level on the PSNR index, which indicates that some noise is present in the fusion process. However, due to the specificity of PSNR, the score cannot be completely aligned with the visual quality perceived by the human eye. The sensitivity of human vision to errors is not absolute, and its perception can be influenced by several factors and variations. In the context of the fusion of bronze mirrors, it is important to focus on the visual perception of the human eye. Therefore, the PSNR index ranking can be considered acceptable. Figure 14 represents the visualization of six evaluation indicators for the first, second, third, and fourth sets of bronze mirrors in different fusion methods. From the figure, although the method can still be further improved to a certain extent, such as in improving the PSNR value, the method in this chapter has demonstrated significant advantages in bronze mirror image fusion processing. Notably, considering the large difference in some data, the values of Q\({}^{\text{AB}\text{/F}}\), PSNR, and VIF, shown in Figure 14, are proportionally scaled for analysis. In addition, this paper compares the computational costs of the proposed method and the comparison methods. In order to conduct this evaluation fairly, all methods are programmed by MATLAB 2018B and executed on a desktop equipped with an Intel(R) Core(TM) i7-6700 CPU @ 3.40 GHz and 16.00 GB of RAM. Then, the average running time of each method processing the entire bronze mirror images was statistically analyzed and listed in Table 6.