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
Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this p...Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this paper,a novel image distortion metric based on minimal Total Bounded Variation(TBV) is presented.It is clarified that when the restored image approximates to the original clear image,the smaller the TBV is,the better the definition of the restored image is.Furthermore,the difference between the restored image and the original clear image is the smallest when the TBV is minimum.In numerical results,the TBV of the original clear image,blur image and restored image are presented and compared,and the results demonstrate the validity of the distortion metric proposed.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.
基金supported by the Fund of National Science & Technology monumental projects under Grants No.2012ZX03005012,No. 2011ZX03005-004-03,No.2009ZX03003-007
文摘Image definition measurement plays an important role in various image processing applications.And a reliable objective image definition metrics is critical for evaluating the definition of the restored image.In this paper,a novel image distortion metric based on minimal Total Bounded Variation(TBV) is presented.It is clarified that when the restored image approximates to the original clear image,the smaller the TBV is,the better the definition of the restored image is.Furthermore,the difference between the restored image and the original clear image is the smallest when the TBV is minimum.In numerical results,the TBV of the original clear image,blur image and restored image are presented and compared,and the results demonstrate the validity of the distortion metric proposed.
