提出一种新的基于偏微分方程（PDE）的图像放大算法。算法模型由方向扩散、保真项和冲击滤波构成。通过设置与边缘信息有关的保真项系数，调节图像被模糊的程度，保留图像特征；综合调节扩散方程和冲击滤波的权重，实现两种PDE的自适应耦合。由于运用连续函数，结合图像内容调节两种PDE的权重，避免了在放大时出现人工痕迹。实验结果表明，此算法在客观指标和主观效果上均优于传统双线性插值和其他同类方法，是一种有效的图像放大算法。

Based on partial differential equations (PDE), we propose a novel image magnification approach which consists of oriented diffusion, fidelity term and shock filter. In a zoomed image, the blurring can be adjusted and the features be preserved by setting the coefficient of the fidelity term related to edges. The weighting of oriented diffusion and shock filter can be balanced through continuous function based on image content. Thus we adaptively combine the two kinds of PDE with minimum artifacts. Experiments demonstrate that the proposed adaptive coupling approach can achieve better result than traditional interpolation methods and other similar methods.