Multi-frame image super-resolution reconstruction based on spatial information weighted fields of experts

Author:

Huang Shuying,Wu Jiajun,Yang YongORCID,Lin Pan

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing,Software

Reference33 articles.

1. Bareja, M. N., & Modi, C. K. (2012). An effective iterative back projection based single image super resolution approach. IEEE Computer Society,14(4), 95–99.

2. Chen, P., Nelson, J., & Tourneret, J. Y. (2017). Toward a sparse Bayesian Markov random field approach to hyperspectral unmixing and classification. IEEE Transactions on Image Processing,26(1), 426–438.

3. Chen, J., Nunez-Yanez, J., & Achim, A. (2011). Video super-resolution using generalized Gaussian Markov random fields. IEEE Signal Processing Letters,19(2), 63–66.

4. Cheng, P., Qiu, Y., Wang, X., & Zhao, K. (2017). A new single image super-resolution method based on the infinite mixture model. IEEE Access,5(9), 2228–2240.

5. Demirel, H., Izadpanahi, S., & Anbarjafari, G. (2009). Improved motion-based localized super resolution technique using discrete wavelet transform for low resolution video enhancement. In Proceedings of European signal processing conference (pp. 1097–1101).

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