Direct stereo radargrammetric processing using massively parallel processing

Synthetic Aperture Radar (SAR) offers many ways to reconstruct digital surface models (DSMs). The two most commonly used methods are SAR interferometry (InSAR) and stereo radargrammetry. Stereo radargrammetry is a very stable and reliable process and is far less affected by temporal decorrelation compared with InSAR. It is therefore often used for DSM generation in heavily vegetated areas. However, stereo radargrammetry often produces rather noisy DSMs, sometimes containing large outliers. In this manuscript, we present a new approach for stereo radargrammetric processing, where the homologous points between the images are found by geocoding large amount of points. This offers a very flexible approach, allowing the simultaneous processing of multiple images and of cross-heading image pairs. Our approach relies on a good initial geocoding accuracy of the data and on very fast processing using a massively parallel implementation. The approach is demonstrated using TerraSAR-X images from Mount Song, China, and from Trento, Italy.