An image magnification method with a Gradient Vector Flow (GVF) constraint-based anisotropic diffusion model is proposed in this letter. A Low-Resolution (LR) image is first magnified using bilinear interpolation, and then an iterative image restoration method, with the use of an ani- sotropic diffusion model and a Gaussian moving-average constraint, is applied to the magnified image. The estimated GVF of a High-Resolution (HR) image can be used to remove the jagged effect and to preserve the textural structure in the image. Meanwhile, the use of the Ganssian moving-average LR model can provide a data fidelity constraint, which renders a magnified image closer to the ideal HR version. Experimental results show that the proposed method can improve the quality of magnified images in terms of both objective and subjective criteria.