# Research on Multi-Scale Fusion Method for Ancient Bronze Ware X-ray Images in NSST Domain
## 4 Conclusions and Discussion  
This study presents a method for fusing X-ray images of bronze wares using pixel-level-based image fusion technology, with a multi-scale morphology gradient in the NSST domain and a local topology CNP system. Indeed, the proposed method has been specifically developed to address the unique requirements of the X-ray imaging process applied to bronze wares. The method takes into consideration the distinct characteristics and \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **LDR** & **NMP** & **F-PCNN** & **LatLRR** & **IVFusion** \\ \hline Avg. runtime (s) & 386.1675 & 105.6395 & 466.0509 & 42.1136 & 99.241 \\ \hline  & PL-NSCT & MMIF & IFE & Proposed & \\ \hline Avg. runtime (s) & 10.6795 & 16.5562 & 0.5872 & 11.2355 & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average running time (in seconds) across different methods. Figure 14: Visualization of six evaluation indicators for four sets of bronze mirror images across different fusion methods. (**a**) The first set of bronze mirror images; (**b**) the second set of bronze mirror images; (**c**) the third set of bronze mirror images; (**d**) the fourth set of bronze mirror images. requirements associated with cultural relics research and preservation efforts. By tailoring the fusion approach to suit the particularities of bronze wares, the method can effectively enhance the quality of X-ray images and assist in the analysis, research, and conservation of these valuable cultural relics. In high-frequency information fusion, using MSMG to represent the nature of the contrast strength between the pixels in the image and their neighboring pixels can be combined with WSEML. This combination ensures that the detail information of the source image is fully retained. Notably, this approach is well-suited for bronze wares research and conservation work, as it enables the scientific and comprehensive analysis of bronze wares. For the fusion of low-frequency information, a local topology CNP system is employed. This system draws inspiration from the impulse discharge mechanism of coupled neurons. The rich complementary information within the system can stimulate more local neuron discharges, resulting in enhanced clarity in the corresponding regions of the fused image. In this study, a comparative analysis was conducted using four groups of eight Han Dynasty bronze mirror X-ray images and eight multi-scale fusion methods from the control group experimental data. According to the experiment, the AG, MI, Q\({}^{\text{AB/F}}\), and VIF indicators showed an average increase of 4%. The objective was to effectively retain the maximum degree of information related to the bronze mirror rim disease and mirror center decoration. This method fulfills the observation and protection requirements for the detailed features and conditions of bronze mirror jewelry. It enhances the edge and detail information within the image, thereby fully demonstrating the research value of bronze mirrors. This method reduces the difficulty of analyzing non-destructive testing of X-ray images of bronze mirrors. It provides a solution to the problems existing in X-ray non-destructive testing of bronze mirrors, helping to study and preserve the characteristics of bronze mirrors in cultural relic research and protection. As the research progresses, a meaningful direction for further research in the field has been identified. The image evaluation indicators used in this paper are universal evaluation indicators, and the differences in bronze mirror types and thicknesses currently studied are relatively small. To accommodate the analysis of more complex, three-dimensional large-scale bronze artifacts, it is necessary to add depth operators to the evaluation operators for analysis. In the future, through in-depth research in this direction, the methods proposed in this paper can provide more valuable assistance for the protection and repair of bronze mirrors and even large bronze artifacts. Conceptualization, M.W. ; methodology, M.W. and L.Y. ; software, L.Y.