Multiframe motion coupling for video super resolution
Geiping J, Dirks H, Cremers D, Moeller M (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 10746 LNCS
Pages Range: 123-138
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Venice, ITA
ISBN: 9783319781983
DOI: 10.1007/978-3-319-78199-0_9
Abstract
The idea of video super resolution is to use different view points of a single scene to enhance the overall resolution and quality. Classical energy minimization approaches first establish a correspondence of the current frame to all its neighbors in some radius and then use this temporal information for enhancement. In this paper, we propose the first variational super resolution approach that computes several super resolved frames in one batch optimization procedure by incorporating motion information between the high-resolution image frames themselves. As a consequence, the number of motion estimation problems grows linearly in the number of frames, opposed to a quadratic growth of classical methods and temporal consistency is enforced naturally. We use infimal convolution regularization as well as an automatic parameter balancing scheme to automatically determine the reliability of the motion information and reweight the regularization locally. We demonstrate that our approach yields state-of-the-art results and even is competitive with machine learning approaches.
Involved external institutions
Westfälische Wilhelms-Universität (WWU) Münster
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
Universität Siegen
Germany (DE)
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
Universität Siegen
Germany (DE)
How to cite
APA:
Geiping, J., Dirks, H., Cremers, D., & Moeller, M. (2018). Multiframe motion coupling for video super resolution. In Marcello Pelillo, Edwin Hancock (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 123-138). Venice, ITA: Springer Verlag.
MLA:
Geiping, Jonas, et al. "Multiframe motion coupling for video super resolution." Proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMVCPR 2017, Venice, ITA Ed. Marcello Pelillo, Edwin Hancock, Springer Verlag, 2018. 123-138.
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