## 3 Experimental Results
### Experimental Results for Wuhan
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & **Band** & **STARFM** & **FSDAF** & **Fit-FC** & **EDCSTFN** & **GAN-STFM** & **MLFF-GAN** & **STF-Trans** & **CTSTFM** & **Proposed** \\ \hline \multirow{8}{*}{RMSE} & 1 & 0.0143 & 0.0149 & **0.0140** & 0.0151 & 0.0146 & 0.0161 & 0.0142 & 0.0167 & 0.0143 \\  & 2 & 0.0200 & 0.0207 & 0.0201 & **0.0200** & 0.0207 & 0.0223 & 0.0203 & 0.0234 & 0.0214 \\  & 3 & 0.0251 & 0.0258 & **0.0251** & 0.0257 & 0.0264 & 0.0269 & 0.0260 & 0.0320 & 0.0256 \\  & 4 & 0.0376 & 0.0397 & 0.0385 & 0.0394 & 0.041 & 0.0400 & 0.0360 & 0.0532 & **0.0351** \\  & 5 & 0.0568 & 0.0621 & 0.0565 & 0.0590 & 0.054 & 0.0533 & 0.0574 & 0.0660 & **0.0503** \\  & 6 & 0.0455 & 0.0515 & 0.0446 & 0.0407 & 0.0399 & 0.0404 & 0.0411 & 0.0476 & **0.0372** \\  & Avg & 0.0332 & 0.0358 & 0.0331 & 0.0333 & 0.0328 & 0.0332 & 0.0325 & 0.0398 & **0.0306** \\ \hline \multirow{8}{*}{SSIM} & 1 & 0.9132 & 0.9125 & 0.9233 & 0.9228 & 0.9185 & 0.9059 & 0.9217 & 0.9166 & **0.9268** \\  & 2 & 0.8730 & 0.8709 & 0.8800 & **0.8897** & 0.8801 & 0.8709 & 0.8856 & 0.8843 & 0.8888 \\  & 3 & 0.8350 & 0.8331 & 0.8438 & 0.8455 & 0.8413 & 0.8356 & 0.8498 & 0.8391 & **0.8562** \\  & 4 & 0.7292 & 0.7294 & 0.7405 & 0.7083 & 0.7037 & 0.7239 & 0.7409 & 0.6910 & **0.7593** \\  & 5 & 0.5697 & 0.5220 & 0.5532 & 0.5513 & 0.5696 & 0.5948 & 0.5797 & 0.5766 & **0.6241** \\  & 6 & 0.6408 & 0.5754 & 0.6274 & 0.6267 & 0.6438 & 0.6533 & 0.6481 & 0.6473 & **0.6595** \\  & Avg & 0.7601 & 0.7405 & 0.7614 & 0.7574 & 0.7595 & 0.7641 & 0.7710 & 0.7591 & **0.7908** \\ \hline \multirow{8}{*}{UUQI} & 1 & 0.7152 & 0.7062 & 0.7124 & 0.6132 & 0.6844 & 0.6839 & 0.7313 & 0.5813 & **0.7354** \\  & 2 & 0.7019 & 0.6890 & 0.6943 & 0.6560 & 0.6807 & 0.7125 & **0.7283** & 0.5637 & 0.7262 \\  & 3 & 0.7072 & 0.6965 & 0.7007 & 0.6573 & 0.696 & 0.7179 & 0.7184 & 0.5366 & **0.7541** \\  & 4 & 0.7857 & 0.7794 & 0.7827 & 0.7431 & 0.766 & 0.7826 & 0.8193 & 0.6991 & **0.8370** \\  & 5 & 0.7531 & 0.7198 & 0.7313 & 0.6645 & 0.7659 & 0.7940 & 0.7663 & 0.7436 & **0.8169** \\  & 6 & 0.7205 & 0.6531 & 0.7021 & 0.7316 & 0.7798 & 0.7918 & 0.7849 & 0.7713 & **0.8215** \\  & Avg & 0.7306 & 0.7073 & 0.7206 & 0.6776 & 0.7288 & 0.7471 & 0.7581 & 0.6493 & **0.7818** \\ \hline \multirow{8}{*}{CC} & 1 & 0.7158 & 0.7076 & 0.7160 & 0.6582 & 0.6878 & 0.6870 & 0.7322 & 0.6073 & **0.7363** \\  & 2 & 0.7071 & 0.6916 & 0.7007 & 0.6958 & 0.6888 & 0.7169 & 0.7283 & 0.5902 & **0.7293** \\ \cline{1-1}  & 3 & 0.7130 & 0.7004 & 0.7086 & 0.6834 & 0.6994 & 0.7192 & 0.7188 & 0.5469 & 0.7564 \\ \cline{1-1}  & 4 & 0.8075 & 0.8011 & 0.8098 & 0.7832 & 0.769 & 0.7871 & 0.8300 & 0.7243 & **0.8375** \\ \cline{1-1}  & 5 & 0.7090 & 0.7666 & 0.7832 & 0.7695 & 0.7864 & 0.7993 & 0.8109 & 0.7750 & **0.8282** \\ \cline{1-1}  & 6 & 0.7873 & 0.7473 & 0.7786 & 0.7871 & 0.7883 & 0.7977 & 0.8153 & 0.7949 & **0.8293** \\ \cline{1-1}  & Avg & 0.7536 & 0.7358 & 0.7495 & 0.7295 & 0.7366 & 0.7512 & 0.7726 & 0.6731 & **0.7862** \\ \hline ERGAS & ALL & 2.0655 & 2.2230 & 2.0322 & 2.0245 & 1.9837 & 2.0300 & 1.9938 & 2.3816 & **1.8816** \\ \hline SAM & ALL & 16.2826 & 17.0293 & 16.2303 & 16.8170 & 16.7738 & 16.5577 & 15.9620 & 18.0406 & **15.3922** \\ \hline \hline \end{tabular}  
* The best values of the index are marked in bold.  
\end{table} 
Table 2: Quantitative evaluation results with different methods on the LGC dataset. is more sensitive to changes in the water boundary than the spatial detail enhancement-focused STF-Trans and CTSTFM. Furthermore, it demonstrates superior overall detail reconstruction compared to the temporal change-focused EDCSTFN. Table 3 presents a quantitative comparison of fusion results on the Wuhan dataset. EDCSTFN achieves the highest CC metric; however, its performance on other metrics is less competitive, indicating that although EDCSTFN-generated images align well with the overall trends of the real images, they contain relatively large local errors. In contrast, the