3D reconstruction from multi-view VHR-satellite images in MicMac

Ewelina Rupnik (1, 2) , Marc Pierrot-Deseilligny (3) , Arthur Delorme (2)

1 LaSTIG - Laboratoire des Sciences et Technologies de l'Information Géographique
2 IPGP - Institut de Physique du Globe de Paris
3 MATIS - Méthodes d'Analyses pour le Traitement d'Images et la Stéréorestitution

Keywords: VHR-satellite imagery Multi-view Bundle block adjustment Dense image matching Depth map fusion a b s t r a c t This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

Domaines: Sciences de l'environnement; Traitement du signal et de l'image [eess.SP]

Ewelina Rupnik, Marc Pierrot-Deseilligny, Arthur Delorme. 3D reconstruction from multi-view VHR-satellite images in MicMac. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, ⟨10.1016/j.isprsjprs.2018.03.016⟩. ⟨hal-02369304⟩