Algorithm of Compressed Video Super-resolution Restoration Based on Bayesian Theory
基于Bayesian理论的压缩视频超分辨率重构算法

At first an acquisition of the compressed video model is proposed,then the super-resolution problem is for mulated within the Bayesian framework and the MAP(maximum posterior probability) criterion,finally a universal solution of the problem is presented by integrating the CCD(cyclic coordinate decent) with SA(successive approximations).In order to resolve the problem that the original high-resolution's quality-reduce function is always unknown,a new estimation method is introduced based on the EM(expectation-maximization) algorithm.The results of the experiment demonstrate that the algorithm not only outperforms the traditional ones on the aspects of PSNR and restoration vision effect,but also has the characteristic of easy extension.