In this paper,we introduce a novel hybrid variational model which generalizes the classical total variation method and the wavelet shrinkage method.An alternating minimization direction algorithm is then employed.We a...In this paper,we introduce a novel hybrid variational model which generalizes the classical total variation method and the wavelet shrinkage method.An alternating minimization direction algorithm is then employed.We also prove that it converges strongly to the minimizer of the proposed hybrid model.Finally,some numerical examples illustrate clearly that the new model outperforms the standard total variation method and wavelet shrinkage method as it recovers better image details and avoids the Gibbs oscillations.展开更多
基金supported by RGC 203109,RGC 201508the FRGs of Hong Kong Baptist Universitythe PROCORE-France/Hong Kong Joint Research Scheme sponsored by the Research Grant Council of Hong Kong and the Consulate General of France in Hong Kong F-HK05/08T.
文摘In this paper,we introduce a novel hybrid variational model which generalizes the classical total variation method and the wavelet shrinkage method.An alternating minimization direction algorithm is then employed.We also prove that it converges strongly to the minimizer of the proposed hybrid model.Finally,some numerical examples illustrate clearly that the new model outperforms the standard total variation method and wavelet shrinkage method as it recovers better image details and avoids the Gibbs oscillations.
