## 3 Methods
### Bundle-Block Adjustment  
As indicated in the literature, the PSS images are well oriented and described by RFMs, represented through RPCs. The RPC bias correction, i.e., correction of errors in camera position and orientation, could be solved via bundle-block adjustment (_bundle_adjust_) and is expected to result in a residual bias of less than one pixel. The adjustment minimizes the reprojection error between estimated back-projected pixel positions of 3D object points and their actual measured positions in the images [28]. For this purpose, feature point detection and matching are performed for all selected image pairs using the default OBAloG algorithm [32]. These matched points are triangulated into 3D surface points using the provided RPCs. To optimize performance, the number of interest points is limited to the top 5000. Given the anticipated minimal bias, the weighting is configured to allow only minor adjustments to the sensor poses. Outliers in the image matching are excluded through RANSAC, which is used in the course of computing the fundamental matrices. For triangulation, outliers are filtered by rejecting 3D points with intersection angles below the specified minimum convergence angle. Additionally, 3D points are classified as outliers if their calculated elevations exceed the possible range, which is determined by the minimum and maximum elevations of the approximation DEM \(\pm\) an elevation limit threshold (see Table 1). Images that could not be aligned during bundle-block adjustment are rejected from further processing. Consequently, potential corresponding image pairs that include these images are also excluded. The default settings have been retained  
\begin{table}
\begin{tabular}{l c l l} \hline
**Parameter** & **Type** & **Description** & **Default** \\ \hline \multirow{3}{*}{pss\_band} & \multirow{3}{*}{int} & Specifies the band used for stereo reconstruction. The Near-Infrared (NIR, Band 4) is recommended for improved contrast in saturated areas, such as snow. & \multirow{3}{*}{4} \\  & & & \\ \hline no\_ortho & \multirow{3}{*}{bool} & Disable orthorectification before stereo reconstruction (not recommended). & \multirow{3}{*}{False} \\ \hline elevation\_tolerance & \multirow{3}{*}{float} & Elevation tolerance [m] for filtering out coarse outliers in bundle-block adjustment & \multirow{3}{*}{500.0} \\ \hline min\_convergence\_angle & \multirow{3}{*}{float} & Minimum convergence angle [deg] between two PSS images. & \multirow{3}{*}{4.0} \\ \hline min\_overlap\_percent & \multirow{3}{*}{float} & Minimum overlap percentage between two PSS images (0.0–1.0 \(\equiv\) 0–100\%). & \multirow{3}{*}{0.1} \\ \hline subpx\_kernel & \multirow{3}{*}{int} & Subpixel kernel size ([px], use larger values for Bayes EM or low-texture images). & \multirow{3}{*}{35} \\ \hline corr\_kernel & \multirow{3}{*}{int} & Correlation kernel size ([px], use odd value, 3–9 for SGM or MGM methods). & \multirow{3}{*}{7} \\ \hline \end{tabular}
\end{table}
Table 1: Expert settings.  
for all other parameters used in _(bundle_adjust)_. The estimated correction values for the sensor poses are output as translation and rotation adjustments for each scene. These corrections are automatically applied by ASP to the respective RPCs during subsequent processing steps.