ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-1, 121-128, 2016
https://doi.org/10.5194/isprs-annals-III-1-121-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
02 Jun 2016
AUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA
C. Platias, M. Vakalopoulou, and K. Karantzalos Remote Sensing Laboratory, National Technical University of Athens, Zographou campus, 15780, Athens, Greece
Keywords: Video Sequence, Co-registration, Descriptors, Deformable Registration, STAR, FREAK Abstract. 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.
Conference paper (PDF, 2526 KB)


Citation: Platias, C., Vakalopoulou, M., and Karantzalos, K.: AUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-1, 121-128, https://doi.org/10.5194/isprs-annals-III-1-121-2016, 2016.

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