Adaptive Charbonnier Superresolution Method with Robust Edge Preservation Capabilities
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Date
2013
Journal Title
Journal ISSN
Volume Title
Publisher
International Society for Optics and Photonics
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
Maiseli, B.J., Liu, Q., Elisha, O.A. and Gao, H., 2013. Adaptive Charbonnier superresolution method with robust edge preservation capabilities. Journal of Electronic Imaging, 22(4), pp.043027-043027.