Large-scale automatic block adjustment from satellite to indoor photogrammetry

Abstract

ABSTRACT Block Adjustment (BA) is a critical procedure in the geometric processing of satellite images, responsible for compensating and correcting the geometric positioning errors of the images. The accuracy of the photogrammetric products, including Digital Orthophoto Map (DOM), Digital Elevation Model (DEM), Digital Line Graphic (DLG), and Digital Raster Graphic (DRG), directly depends on the accuracy of BA results. In recent years, the rapid development of related technologies such as Artificial Intelligence (AI), Computer Vision (CV), Unmanned Aerial Vehicles (UAVs) and big data has greatly facilitated and transformed the classical BA in photogrammetry. This paper first reviews the current status of BA and then looks into the future. First, this paper provides a brief review of the key technologies involved in BA, including image matching, the establishment of adjustment model, the determination of the parameters and the detection of gross error. Then, taking the intercross and fusion of current technologies such as AI, cloud computing and big data with photogrammetry into account, this paper explores the future trends of photogrammetry. Finally, four typical cases of large-scale adjustment are introduced, including large-scale BA without Ground Control Points (GCPs) for optical stereo satellite images, large-scale BA with laser altimetry data for optical stereo satellite images, large-scale BA for UAV oblique photogrammetry, and large-scale BA for indoor photogrammetry in caves with a large number of close-range images.