# Utilization of Merge-Sorting Method to Improve Stitching Efficiency in Multi-Scene Image Stitching
## 6 Conclusions  
In contrast to the traditional image stitching method, a multi-scene image stitching method based on the merge-sorting model was proposed in this paper. The bottom-up stitching method is adopted for the input image to construct the merge-sorting model, and the root-node image in the merge-sorting model is the final stitched image. For image registration, the A-KAZE features are extracted first, and then the feature points are matched using the bidirectional KNN algorithm. This makes it possible to avoid spending a lot of time with image registration and improves the efficiency of image registration. When there are two images that match well, this method stitches them directly without sorting, which greatly reduces the number of registrations of unrelated images. The experimental results show that the proposed method can improve the efficiency of image stitching, enhance the robustness of image registration, and reduce the distortion in the stitched images. The MSIS method improves the stitching efficiency and reduces the distortion in the images after stitching. However, the image registration takes a long time throughout the process. In addition, stitched images have black boundary bars, and there are performance limitations relating to the device used for processing. In the future, we will continue our research and further reduce the time required for image registration. For image fusion, we will continue to investigate the black bars shown in Figure 7 and upgrade the corresponding processing equipment.  
**Author Contributions:** Methodology, W.L.; writing--original draft, W.L.; software, W.L. and J.H.; supervision, B.S.; writing--review and editing, K.Z., Y.Z. and J.H.; validation, K.Z.; funding acquisition, B.S.; investigation, B.S.; project administration, B.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China, grant number 32271248.  
**Institutional Review Board Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Scene**} & \multirow{2}{*}{\begin{tabular}{c} **Number of** \\ **Experiments** \\ \end{tabular} } & \multicolumn{4}{c}{**Time Spent Stitching Images**} \\ \cline{3-5}  & & **Binary Tree-Based** & **Left-to-Right** & **MSIS** \\ \hline \multirow{4}{*}{\begin{tabular}{c} Scene 1 \\ (8 images) \\ \end{tabular} } & 1 & 736 & 525 & 626 \\ \cline{2-5}  & 2 & 720 & 517 & 512 \\ \cline{2-5}  & 3 & 738 & 497 & 502 \\ \cline{2-5}  & 4 & 747 & 503 & 513 \\ \cline{2-5}  & 5 & 712 & 505 & 518 \\ \hline \multirow{2}{*}{\begin{tabular}{c} Average \\ \end{tabular} } & 6 & 730 & **509** & 534 \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Scene 2 \\ (14 images) \\ \end{tabular} } & 1 & 734 & 798 & 665 \\ \cline{2-5}  & 2 & 725 & 803 & 654 \\ \cline{2-5}  & 3 & 730 & 813 & 659 \\ \cline{2-5}  & 4 & 718 & 806 & 648 \\ \cline{2-5}  & 5 & 720 & 810 & 655 \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Average \\ \end{tabular} } & 6 & 725 & 806 & **656** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Time required for stitching images with each method for the two experimental scenes (unit: s).  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** No new data were created or analyzed in this study.  
**Acknowledgments:** The authors thank the staff from the Experimental Auxiliary System and the Information Center of Shanghai Synchrotron Radiation Facility (SSRF) for on-site assistance with the GPU computing system.  
**Conflicts of Interest:** The authors declare no conflict of interest.