This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the M...This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the MAP is done by minimizing the energy functional, The half-quadratic regularization method is used to solve the corresponding partial differential equations （PDEs）, This approach gives the improved results over the conventional de-interlacing methods, Two criteria are proposed in the paper, and they can be used to evaluate the performance of the de-interlacing algorithms,展开更多
In this paper, a generalized augmented Lagrangian-successive over-relaxation （GAL- SOR） iteration method is presented for solving saddle-point systems arising from distributed control problems. The convergence prope...In this paper, a generalized augmented Lagrangian-successive over-relaxation （GAL- SOR） iteration method is presented for solving saddle-point systems arising from distributed control problems. The convergence properties of the GAL-SOR method are studied in the spectral properties for the precondidetail. Moreover, when0 ≤ω≤ 1 and Q=1/γI , tioned matrix are analyzed. Numerical experiments show that if the mass matrix from the distributed control problems is not easy to inverse and the regularization parameter β is very small, the GAL-SOR iteration method can work well.展开更多
文摘This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the MAP is done by minimizing the energy functional, The half-quadratic regularization method is used to solve the corresponding partial differential equations （PDEs）, This approach gives the improved results over the conventional de-interlacing methods, Two criteria are proposed in the paper, and they can be used to evaluate the performance of the de-interlacing algorithms,
基金Acknowledgements. The authors are very much indebted to the referees for providing very valuable suggestions and comments, which greatly improved the original manuscript of this paper. This work was supported by the National Natural Science Foundation of China （No. 11271174 and No. 11511130015） and the Scientific Research Project of Putian University （No. 2015061）.
文摘In this paper, a generalized augmented Lagrangian-successive over-relaxation （GAL- SOR） iteration method is presented for solving saddle-point systems arising from distributed control problems. The convergence properties of the GAL-SOR method are studied in the spectral properties for the precondidetail. Moreover, when0 ≤ω≤ 1 and Q=1/γI , tioned matrix are analyzed. Numerical experiments show that if the mass matrix from the distributed control problems is not easy to inverse and the regularization parameter β is very small, the GAL-SOR iteration method can work well.
