Image magnification method with GVF-based anisotropic diffusion model

An image magnification method with GVF-based anisotropic diffusion model is proposed. An image is magnified by bilinear interpolation at first. Then, an iterative restoration with a GVF based mean curvature flow diffusion and a Gaussian moving average LR constraint is applied to the magnified image. Since GVF is a rotational field, as an external force field to descript the edges of an image, the vector flow will become streamline near the jagged edges. Therefore, the GVF based anisotropic diffusion will be helpful to remove the jagged effects as well as keep the texture structures. Meanwhile, the Gaussian moving average LR model provides a data fidelity constraint which makes the results more close to the ideal HR images. Experiments results show that the proposed method can improve the quality of magnified image in terms of both the objective and subjective.