Multi-image matching for DSM generation from IKONOS imagery

Abstract High-resolution satellite images at sub-5-m footprint, such as IKONOS and SPOT5 HRG/HRS images, are becoming increasingly available to the earth observation community and their respective clients. The related cameras all use linear array CCD technology for image sensing. The processing of these kinds of images provides a challenge for algorithmic redesign and this offers the possibility of reconsidering and improving many photogrammetric processing components. This contribution presents an advanced matching approach for automatic DSM generation from high-resolution satellite images. It can provide dense, precise and reliable results. The method matches multiple (more than two) images simultaneously and it uses a coarse-to-fine hierarchical solution with an effective combination of several image matching algorithms and automatic quality control. The DSMs are generated by a combination of matching results of feature points, grid points and edges. The proposed approach has been applied to IKONOS images over a testfield in Thun, Switzerland with accurate ground control points, a 1600-m height range and variable land cover, but with sub-optimal imaging conditions (snow, long shadows). The accuracy tests are based on the comparison between the reference data from an airborne laser scanner and the automatically extracted DSMs. The RMS errors for the whole area, excluding trees and bushes, are 2–3 m, while for bare ground the accuracy is about 1 m or even better.