Adaptive non-convex total variation regularisation for image restoration

Adaptive non-convex total variation regularisation for image restoration

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An adaptive non-convex total variation regularisation is proposed for blind image restoration. A flux corrected transport (FCT) technique is used to obtain a stable numerical scheme, where a spatially varying constraint allows a better restoration of image edges and fine detail. Finally, its advantages are shown in deblurring edges, denoising and restoring fine details of image simultaneously in experiments.


    1. 1)
      • T. Chan , J. Shen . (2005) Image processing and analysis: variational, PDE, wavelet, and stochastic methods.
    2. 2)
      • A. Tikhonov , V. Arsenin . (1977) Solutions of Ill-posed problems.
    3. 3)
    4. 4)
      • S. Fu , Q. Ruan , W. Wang , F. Gao , H. Cheng . A feature-dependent fuzzy bidirectional flow for adaptive image sharpening. Neurocomputing , 883 - 895
    5. 5)
      • G. Gilboa . Nonlinear scale space with spatially varying stopping time. IEEE Trans. Pattern Anal. Mach. Intell. , 12 , 2175 - 2187
    6. 6)
      • S. Osher , R. Fedkiw . (2002) Level set methods and dynamic implicit surfaces.

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