基于通用高斯马尔可夫随机场模型的图像超分辨率重建

提出了一种基于通用高斯马尔可夫随机场（0孙皿疆）模型的图像超分辨率重建方法，给出了求解过程和实验结果，并进行了分析。相对Compound Markov随机场模型和Huber-Markov随机场模型，GGMRF模型不用判断边缘或者线过程，因此优化求解简单，大大减少了运算量。实验结果表明在低噪声情况下，该方法重建图像视觉效果较好。

Reconstruction of Superresolution Image Using Generalized Gaussian Markov Random Fields Model

An image super-resolution reconstruction method based on generalized Gauss-Markov random fields (GGM- RF)model is presented in this paper. The process of searching solution and experimental results are presented and ana- lyzed. Compared with Compound Markov and Huber-Markov random models, GGMRF model has the merits of easier solving and reduced computational expense, because it does not need to discriminate edge or line process. The experi- mental results show that for the case of lightly noised image, this method has a better visual effect on the reconstructed image.