# End-to-End Online Video Stitching and Stabilization Method Based on Unsupervised Deep Learning
## 3 Experimental Results and Analysis
### Ablation Experiments

Table 6: Ablation study on the selection of parameter \(\alpha_{\text{s}}\) (“\(\uparrow\)” means higher values are better for the metric). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\beta_{\text{s}}\) & **Stability \(\uparrow\)** & **Distortion \(\uparrow\)** & \
\begin{tabular}{c} **Alignment** \\ **(PSNR/SSIM) \(\uparrow\)** \\ \end{tabular} &
\begin{tabular}{c} **Description** \\ \end{tabular} \\ \hline
0 & 0.9124 & 0.8296 & 30.13/0.887 &
\begin{tabular}{c} Shooothed trajectory \\ deviates from original \\ path; high distortion. \\ Split deviation. \\ Balanced. \\ Higher fidelity; slightly \\ reduced stability. \\ Overfitting; partial \\ discontinuities. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Ablation study on the selection of parameter \(\beta_{\text{s}}\). (“\(\uparrow\)” means higher values are better for the metric). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Absolute Path** & **Relative Path** & **Alignment \(\uparrow\)** & **Distortion \(\uparrow\)** & **Stability \(\uparrow\)** \\ \hline ✓ & & 30.35/0.893 & 0.8357 & 0.8718 \\ ✓ & ✓ & 30.41/0.893 & 0.8418 & 0.8997 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Ablation studies on alignment, distortion, and stability. (“\(\uparrow\)” means higher values are better for the metric). In addition, a sensitivity analysis was conducted on the weighting parameters \(\lambda_{0}\) and \(\beta\), which control the influence of photometric alignment and temporal consistency, respectively. By systematically varying \(\lambda_{0}\) while fixing \(\beta\), and vice versa, we observed that improper values can significantly affect convergence behavior and alignment accuracy. The results, summarized in Tables 9 and 10, confirm that the selected default values strike an optimal balance between training efficiency and reconstruction quality. These findings reinforce the robustness of the proposed framework across a range of parameter settings. Based on the above ablation experiment results and the visual effect comparison, it is evident that our method outperforms existing advanced methods in all metrics through the overall end-to-end training strategy, dual-input smoothing module, and relative path calculation mechanism. This not only verifies the rationality of each module design but also further proves the feasibility and superiority of achieving efficient video stitching and stabilization in dynamic and complex scenes. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\beta\) &
\begin{tabular}{c} **Epochs to** \\ **Converge** \\ \end{tabular} & **PSNR** & **SSIM** & **Description** \\ \hline
1 & 13 & 29.08 & 0.887 &
\begin{tabular}{c} Fast convergence, but \\ alignment is average. \\ \end{tabular} \\
2 & 16 & 29.76 & 0.890 &
\begin{tabular}{c} Slow improvement; \\ moderate convergence. \\ \end{tabular} \\
5 (default) & 22 & 30.41 & 0.893 &
\begin{tabular}{c} Best balance. \\ Slow convergence; scores \\ slightly decreased. \\ \end{tabular} \\
10 & 37 & 29.55 & 0.889 &
\begin{tabular}{c} Slow convergence; \\ Slowest convergence; \\ scores also decreased. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Ablation experiments on the selection of parameter \(\beta\). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\gamma_{s}\) & **Stability \(\uparrow\)** & **Distortion \(\uparrow\)** &
\begin{tabular}{c} **Alignment** \\ **(PSNR/SSIM) \(\uparrow\)** \\ \end{tabular} & **Description** \\ \hline
0 & 0.8921 & 0.8439 & 30.44/0.892 &
\begin{tabular}{c} Boundary jumps at the \\ edges of long sequences. \\ \end{tabular} \\
10 & 0.8963 & 0.8427 & 30.43/0.893 &
\begin{tabular}{c} Slightly better. \\ Best balance. \\ \end{tabular} \\
30 (default) & 0.8997 & 0.8418 & 30.41/0.893 &
\begin{tabular}{c} Best balance. \\ Overly smoothed \\ overall; slight drop in \\ main performance. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Ablation study on the selection of parameter \(\gamma_{s}\). (“\(\uparrow\)” means higher values are better for the metric).