## 5 Conclusions  
In this paper, we propose an improved 3D reconstruction method for satellite images based on GAN image enhancement, which uses the perceptual loss function training network to enhance the satellite image. The loss function of the proposed method is a good combination of MSE loss, VGG loss, adversarial loss, and regularization loss. This method improves the quality of satellite images and then improves the accuracy of the reconstruction results of the satellite images. The proposed method in this paper not only obtains 3D point clouds with good visual quality but also has a good objective quality evaluation of the reconstruction results. Comparative experiments with other methods prove the effectiveness and feasibility of the proposed method.  
Conceptualization, H.L. and J.Y.; methodology, H.L. and L.J.; software, H.L.; validation, H.L.; formal analysis, H.L., L.J. and J.Y.; investigation, H.L. and L.J.; resources, H.L.; data curation, H.L.; writing--original draft preparation, H.L.; writing--review and editing, H.L., L.J. and J.Y.; visualization, H.L. and L.J.; supervision, J.Y.; project administration, J.Y.; funding acquisition, H.L. and J.Y. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Site** & **Method** & **CP (\%)** & **RMSE (m)** & **ME (m)** \\ \hline \multirow{3}{*}{1} & S2P method [7] & 73.98 & 2.60 & 0.39 \\  & BA method [18] & 72.60 & 2.68 & 0.65 \\  & Proposed method & 74.69 & 2.47 & 0.42 \\ \hline \multirow{3}{*}{2} & S2P method [7] & 60.77 & 2.74 & 0.57 \\  & BA method [18] & 60.66 & 2.64 & 0.55 \\  & Proposed method & 65.08 & 2.22 & 0.50 \\ \hline \multirow{3}{*}{3} & S2P method [7] & 67.21 & 8.87 & 0.35 \\  & BA method [18] & 66.91 & 3.99 & 0.47 \\  & Proposed method & 68.88 & 5.58 & 0.34 \\ \hline \multirow{3}{*}{4} & S2P method [7] & 50.21 & 11.14 & 0.98 \\  & BA method [18] & 42.04 & 9.34 & 1.45 \\  & Proposed method & 51.50 & 10.74 & 0.89 \\ \hline \multirow{3}{*}{5} & S2P method [7] & 71.19 & 1.92 & 0.52 \\  & BA method [18] & 68.61 & 2.31 & 0.46 \\  & Proposed method & 71.45 & 1.88 & 0.51 \\ \hline \multirow{3}{*}{6} & S2P method [7] & 68.57 & 2.17 & 0.53 \\  & BA method [18] & 53.02 & 3.74 & 0.90 \\  & Proposed method & 68.74 & 2.17 & 0.54 \\ \hline \multirow{3}{*}{7} & S2P method [7] & 59.20 & 7.56 & 0.74 \\  & BA method [18] & 54.71 & 6.37 & 0.82 \\ \cline{1-1}  & Proposed method & 58.67 & 4.97 & 0.74 \\ \hline \multirow{3}{*}{8} & S2P method [7] & 63.12 & 5.03 & 0.47 \\  & BA method [18] & 62.66 & 3.80 & 0.66 \\ \cline{1-1}  & Proposed method & 63.34 & 4.85 & 0.48 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The quality evaluation results of the reconstructed results.  
**Funding:** This work has been supported by Major Program of National Natural Science Foundation of China NSFC (Nos.122929980, 12292984); by National Key R&D Program of China (Nos. 2023 YFA1009000, 2023 YFA1009004, 2020 YFA0712203, 2020 YFA0712201); by Key Projects of National Natural Science Foundation of China NSFC (no. 12031016); by Beijing Natural Science Foundation (no. BNSF-Z210003); by the Department of Science, Technology and Information of the Ministry of Education (no. 8091B042240); and by the Fundamental Research Funds for the Central Universities (2412022 QD024).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.