An image magnification method with a Gradient Vector Flow(GVF)constraint-basedanisotropic diffusion model is proposed in this letter.A Low-Resolution(LR)image is first magnifiedusing bilinear interpolation,and then an...An image magnification method with a Gradient Vector Flow(GVF)constraint-basedanisotropic diffusion model is proposed in this letter.A Low-Resolution(LR)image is first magnifiedusing 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 topreserve the textural structure in the image.Meanwhile,the use of the Gaussian moving-average LRmodel can provide a data fidelity constraint,which renders a magnified image closer to the ideal HRversion.Experimental results show that the proposed method can improve the quality of magnifiedimages in terms of both objective and subjective criteria.展开更多
基金a grant from the Research Grants Council othe Hong Kong Special Administrative Region,China(NoPolyU 5199/06E)by the National Natural ScienceFoundation of China(No.60472036,No.60431020,No60402036,No.60772069)the Natural Science Foundation of Beijing(No.4062006).
文摘An image magnification method with a Gradient Vector Flow(GVF)constraint-basedanisotropic diffusion model is proposed in this letter.A Low-Resolution(LR)image is first magnifiedusing 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 topreserve the textural structure in the image.Meanwhile,the use of the Gaussian moving-average LRmodel can provide a data fidelity constraint,which renders a magnified image closer to the ideal HRversion.Experimental results show that the proposed method can improve the quality of magnifiedimages in terms of both objective and subjective criteria.
