## 4 Experimental Results and Discussion
### Performance Analysis on Satellite Image Pair  
In this section, we select 10 satellite image pairs from the IARPA MVS3 DM dataset to test the proposed method and the effect of the acquisition parameters on DSM generation. The input satellite image and the ground truth DSM are shown in Figure 4. Due to the limited space of the article, we only show one of the input satellite images. As for Figure 4b, we draw the ground truth DSM as an RGB image for visualization. The altitude range is 18-35 m, and the areas with lower altitudes are indicated in blue and the areas with higher altitudes are indicated in red. The geographic range of the input satellite images is slightly larger than that of the ground truth DSM, which is in order to ensure that the geographic range of the generated DSM can fully contain that of the ground truth DSM. The acquisition parameters of the satellite image pairs are listed in Table 2. We choose the acquisition interval, sun angle difference, and intersection angle as the main parameters affecting DSM generation. The acquisition interval has a great influence on the surface buildings and vegetation of the satellite images [20]. In our experiment, the acquisition interval ranges from 1 day to 398 days, which meets the minimum and maximum intervals of the IARPA MVS3 DM dataset. Here the sun angle difference is defined as the root mean square value of the \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Image Pair** & **Acquisition Interval** & **Sun Angle Difference** & **Intersection Angle** \\ \hline
1 & 1 day & 0.07\({}^{\circ}\) & 5.9\({}^{\circ}\) \\
2 & 1 day & 0.16\({}^{\circ}\) & 9.2\({}^{\circ}\) \\
3 & 1 day & 0.22\({}^{\circ}\) & 3.1\({}^{\circ}\) \\
4 & 7 days & 1.41\({}^{\circ}\) & 16.8\({}^{\circ}\) \\
5 & 26 days & 2.34\({}^{\circ}\) & 8.0\({}^{\circ}\) \\
6 & 76 days & 22.29\({}^{\circ}\) & 1.3\({}^{\circ}\) \\
7 & 95 days & 26.83\({}^{\circ}\) & 0.4\({}^{\circ}\) \\
8 & 152 days & 4.10\({}^{\circ}\) & 3.6\({}^{\circ}\) \\
9 & 310 days & 9.31\({}^{\circ}\) & 7.6\({}^{\circ}\) \\
10 & 398 days & 6.13\({}^{\circ}\) & 12.2\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The acquisition parameters of the satellite image pairs. Figure 4: The test data in the IARPA MVS3 DM dataset: (**a**) the input satellite image; (**b**) the ground truth DSM. difference of the sun azimuth angle and the difference of the sun elevation angle, as shown in Equation (7). \[\theta_{sd}=\sqrt{\frac{\theta_{sd}^{2}+\theta_{sd}^{2}}{2}}, \tag{7}\]  
where \(\theta_{sd}\) denotes the sun angle difference, \(\theta_{sad}\) represents the difference of the sun azimuth angle, and \(\theta_{scd}\) stands for the difference of the sun elevation angle. The sun angle difference affects the imaging of the shadow area and specular reflection area of the ground [21]. In this paper, we test the sun angle difference from 0.07\({}^{\circ}\) to 26.83\({}^{\circ}\). Excessive sun angle difference will reduce the number of matched pixels in stereo matching, resulting in the poor-quality DSM, as shown in Figure 5a. The intersection angle of the image pair is a traditional factor that affects stereo matching. We test the intersection angle from 0.4\({}^{\circ}\) to 16.8\({}^{\circ}\). Experimental results with an intersection angle larger than 20\({}^{\circ}\) are not good. The DSM generated by image pairs with an intersection angle of more than 20\({}^{\circ}\) is shown in Figure 5b. The generated DSMs of image pair 1 to image pair 10 are shown in Figure 6. In the experiment, we chose the S2P method [7] to compare with the proposed method. The S2P method is a DSM generation method of satellite images based on geometric stereo rectification, which is one of the methods with the highest accuracy in generating point clouds in recent years, and the s2p 1.0b25 software can be found in [40]. Here we also use the traditional BA method [32] as a comparison method.