A novel regularized adaptive edge-preserving image super-resolution algorithm

YU Hui; CHEN Fu-Sheng; ZHANG Zhi-Jie; WANG Chen-Sheng

doi:10.3724/sp.j.1010.2014.00098

[1] Wallach D, Lamare F, Roux C, et al. Biomedical Imaging: From Nano to Macro,［J］. IEEE International Symposium on, 2009: 931934.

[2] Chan J-W, Ma J, Kempeneers P, et al. Superresolution enhancement of hyperspectral CHRIS/Proba images with a thin-plate spline nonrigid transform model［J］.Geoscience and Remote Sensing, IEEE Transactions on, 2010, 48(6): 25692579.

[3] Huang T S, Tsay R Y. Advances in Computer Vision and Image Processing,［J］. 1984,1(2): 317339.

[4] Park S C, Park M K, Kang M G. Super-resolution image reconstruction: a technical overview［J］.Signal Processing Magazine, IEEE, 2003, 20(3): 2136.

[5] Qin F-q, He X-h, Chen W-l, et al. Video superresolution reconstruction based on subpixel registration and iterative back projection［J］.Journal of Electronic Imaging, 2009, 18(1): 013007013007013011.

[6] Estrela V V, Galatsanos N P. Image Processing, 1998. ICIP 98. Proceedings［C］. 1998 International Conference on, 1998,2: 200203.

[7] Bose N K, Lertrattanapanich S, Koo J. Circuits and Systems, 2001. ISCAS 2001［C］. The 2001 IEEE International Symposium on, 2001,2: 433436.

[8] Krawczyk-StańDo D, Rudnicki M. Regularization parameter selection in discrete ill-posed problems—the use of the U-curve［J］.International Journal of Applied Mathematics and Computer Science, 2007, 17(2): 157164.

[9] Panagiotopoulou A, Anastassopoulos V. Regularized super-resolution image reconstruction employing robust error norms［J］.Optical Engineering, 2009, 48(11): 117004117004117014.