Open AccessAUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA
Author(s) -
C. Platias,
M. Vakalopoulou,
Κωνσταντίνος Καράντζαλος
Publication year - 2016
Publication title -
isprs annals of the photogrammetry, remote sensing and spatial information sciences (cd-rom)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 38
eISSN - 2194-9042
pISSN - 2196-6346
DOI - 10.5194/isprsannals-iii-1-121-2016
Subject(s) - computer science , artificial intelligence , image registration , computer vision , satellite , markov random field , image (mathematics) , image segmentation , engineering , aerospace engineering
In this paper we propose a deformable registration framework for high resolution satellite video data able to automatically and accurately co-register satellite video frames and/or register them to a reference map/image. The proposed approach performs non-rigid registration, formulates a Markov Random Fields (MRF) model, while efficient linear programming is employed for reaching the lowest potential of the cost function. The developed approach has been applied and validated on satellite video sequences from Skybox Imaging and compared with a rigid, descriptor-based registration method. Regarding the computational performance, both the MRF-based and the descriptor-based methods were quite efficient, with the first one converging in some minutes and the second in some seconds. Regarding the registration accuracy the proposed MRF-based method significantly outperformed the descriptor-based one in all the performing experiments.