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Adaptive Charbonnier superresolution method with robust edge preservation capabilities

[+] Author Affiliations
Baraka J. Maiseli

Harbin Institute of Technology, Research Institute of Intelligent Control and Systems, Harbin 150001, China

University of Dar es Salaam, College of Information and Communication Technologies, Department of Electronics and Telecommunication Engineering, P.O. Box 35194, Dar es Salaam, Tanzania

Qiang Liu

Harbin Institute of Technology, Research Institute of Intelligent Control and Systems, Harbin 150001, China

Ogada A. Elisha

Harbin Institute of Technology, Department of Mathematics, Harbin 150001, China

Egerton University, Department of Mathematics, P.O. Box 536, Egerton, Kenya

Huijun Gao

Harbin Institute of Technology, Research Institute of Intelligent Control and Systems, Harbin 150001, China

J. Electron. Imaging. 22(4), 043027 (Dec 16, 2013). doi:10.1117/1.JEI.22.4.043027
History: Received September 9, 2013; Revised October 20, 2013; Accepted November 13, 2013
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Abstract.  Superresolution (SR) is known to be an ill-posed inverse problem, which may be solved using some regularization techniques. We have proposed an adaptive regularization method, based on a Charbonnier nonlinear diffusion model to solve an SR problem. The proposed model is flexible because of its automatic capability to reap the strengths of either linear isotropic diffusion, Charbonnier model, or semi-Charbonnier model, depending on the local features of the image. On the contrary, the models proposed from other research works are fixed and hence less feature dependent. This makes such models insensitive to local structures of the images, thereby producing poor reconstruction results. Empirical results obtained from experiments, and presented here, show that the proposed method produces superresolved images which are more natural and contain well-preserved and clearly distinguishable image structures, such as edges. In comparison with other methods, the proposed method demonstrates higher performance in terms of the quality of images it generates.

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Citation

Baraka J. Maiseli ; Qiang Liu ; Ogada A. Elisha and Huijun Gao
"Adaptive Charbonnier superresolution method with robust edge preservation capabilities", J. Electron. Imaging. 22(4), 043027 (Dec 16, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.4.043027


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