Image Restoration Based on the Hybrid Total-Variation-Type Model

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Baoli Shi; Zhi-Feng Pang; Yu-Fei Yang;

We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two ${L}^{1}$ -norm terms in the proposed model make it difficultly solved by using some classically numerical metho... View more
  • References (53)
    53 references, page 1 of 6

    Aubert, G., Kornprobst, P.. Mathematical Problems in Image Processing. 2002

    Chan, T. F., Shen, J.. Image Processing and Analysis. 2005

    Paragios, N., Chen, Y., Faugeras, O.. The Handbook of Mathematical Models in Computer Vision. 2006

    Engl, H. W., Hanke, M., Neubauer, A.. Regularization of Inverse Problems. 1996; 375

    Rudin, L., Osher, S., Fatemi, E.. Nonlinear total variation based noise removal algorithms. Physica D. 1992; 60: 259-268

    Rudin, L., Osher, S.. Total variation based image restoration with free local constraints. IEEE International Conference on Image Processing. 1994; 1 (13–16): 31-35

    Chan, T. F., Shen, J.. Variational image inpainting. Communications on Pure and Applied Mathematics. 2005; 58 (5): 579-619

    Wagner, R., Smith, S., Sandrik, J., Lopez, H.. Statistics of speckle in ultrasound B-scans. Transactions on Sonics Ultrasonics. 1983; 30 (3): 156-163

    Aubert, G., Aujol, J.-F.. A variational approach to removing multiplicative noise. SIAM Journal on Applied Mathematics. 2008; 68 (4): 925-946

    Montillo, A., Udupa, J., Axel, L., Metaxas, D.. Interaction between noise suppression and inhomogeneity correction in MRI. ; 5032: 1025-1036

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