Super-resolution Reconstruction Based on Regularization
基于正则化处理的超分辨率重建

In this paper, the ill-posed inverse problem of super-resolution reconstruction is concerned. Firstly, the mathematical model of super-resolution reconstruction is given, and the ill-posed property of the least square estimation is analyzed. Then, the regularization of ill-posed problem is processed by modifying the original energy functional, and an adaptive dynamic method is proposed for the choice of the regularization coefficient. Finally, the convergence of the iteration formula and the choice of parameter are thoroughly studied. Experimental results demonstrate the effectiveness of the proposed method.