Alessandra Martins Coelho, Vania Vieira Estrela, Felipe Pereira do Carmo, Sandro Roberto Fernandes, Vania Vieira Estrela, Vania Vieira Estrela, Vania Vieira Estrela, Alessandra Martins Coelho, Sandro Roberto Fernandes, Alessandra Martins Coelho, Sandro Roberto Fernandes, Alessandra Martins Coelho, Alessandra Martins Coelho, Vânia Estrela, Vânia Vieira Estrela, Vania Vieira Estrela. Error concealment by means of motion refinement and regularized bregman divergence. In Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning. Volume 7435 of IDEAL'12, pages 650-657, Springer-Verlag, Berlin, Heidelberg, 2012.
This work addresses the problem of error concealment in video transmission systems over noisy channels employing Bregman divergences along with regularization. Error concealment intends to improve the effects of disturbances at the reception due to bit-errors or cell loss in packet networks. Bregman regularization gives accurate answers after just some iterations with fast convergence, better accuracy and stability. This technique has an adaptive nature: the regularization functional is updated according to Bregman functions that change from iteration to iteration according to the nature of the neighborhood under study at iteration n. Numerical experiments show that high-quality regularization parameter estimates can be obtained. The convergence is sped up while turning the regularization parameter estimation less empiric, and more automatic.