Automatic Dsm Generation from Linear Array Imagery Data

CCD linear array sensors are widely used to acquire panchromatic and multispectral imagery for photogrammetric and remote sensing applications. The processing of this kind of images provides a challenge for algorithmic redesign and this opens the possibility to reconsider and improve many photogrammetric processing components. In addition, the basic capabilities of image matching techniques have so far not been fully utilized yet. This paper presents a matching procedure for automatic DSM generation from linear array imagery data. It can provide dense, precise and reliable results. The method 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 combination of matching results of feature points, grid points and edges. Finally, a modified multi-photo geometrically constrained (MPGC) matching algorithm is employed to achieve sub-pixel accuracy for all the matched features with multi-image or multi-strip image data. The proposed approach in this paper has been applied to different areas with varying textures and terrain types. The accuracy tests are based on the comparison between the high quality DEMs / DSMs derived from airborne Laser Scanner or manual measurements and the automatic extracted DSMs. Results with STARIMAGER, IKONOS and SPOT5 HRS images are reported. We demonstrate with these experiments that our approach leads to good results.