An Effective Regularization Method for Image Super Resolution


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In this paper, we propose a new super resolution (SR) reconstruction method to handle license plate numbers of vehicles in real traffic videos. Recently, SR reconstruction shemes based on regularization have been demonstrated to be effective because SR reconstrction is an ill-posed problem. Working within this promising framework, the residual data (RD) term can be weighted according to the differences among the observed LR images in the SR reconstruction model. Moreover, L1 norm is used to measure the RD term in order to improve the robustness of our method. Experiments show the proposed method improves the subjective visual quality of the high resolution images.



Advanced Materials Research (Volumes 219-220)

Edited by:

Helen Zhang, Gang Shen and David Jin






E. W. Zheng and X. J. Wang, "An Effective Regularization Method for Image Super Resolution", Advanced Materials Research, Vols. 219-220, pp. 1411-1414, 2011

Online since:

March 2011




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