Connectivity-Preserving Control-Network Thinning for Planetary Photogrammetry Using Image-Pair Convex Hulls and Grid Sampling

The dense control networks constructed for regional and global image blocks often contain a substantial number of redundant tie points that increase the computational burden of bundle adjustment (BA). Reducing this redundancy without weakening the geometric support of image pairs is essential for subsequent photogrammetric processing. Existing image-centered network-thinning methods reduce point counts but do not explicitly preserve direct links between individual image pairs. This paper presents an efficient control-network thinning method for planetary photogrammetry based on image-pair convex-hull computation and grid-based interval sampling. The proposed method first organizes the input control network into an image-pair measure map. It then separates each pair’s measures into hull and interior classes using Andrew’s monotone-chain algorithm and samples the two classes at different intervals. When a tie point is selected for an image pair, its measures in both images are retained together. An optional rule can also retain measures of the same surface feature in other overlapping images to help maintain connections across the image block. The method is designed to thin an existing control network after upstream quality filtering. It does not re-evaluate tie-point quality or add new control points. We implemented the method as the cnetoptimize application within the Integrated Software for Imagers and Spectrometers (ISIS), a widely used open-source planetary photogrammetric software system developed by the United States Geological Survey (USGS). Experiments used a large-scale Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) network and a medium-scale Mars Express (MEX) High Resolution Stereo Camera (HRSC) network. At comparable compression ratios, cnetoptimize retained strict non-degenerate support for more image pairs than the image-centered ISIS cnetthinner. Across the tested datasets and settings, cnetoptimize preserved the direct connections of all originally non-degenerate image pairs at compression ratios up to 8.4×. In a downstream test on one weak HRSC pair, bundle adjustment with the thinned cnetoptimize network yielded subpixel image residuals and a local 25 m digital orthophoto map (DOM) seam root mean square (RMS) of 36.0 m. The method provides an ISIS-compatible approach to control-network thinning for planetary mapping.