AN IMAGE MAGNIFICATION ALGORITHM USING THE GVF CONSTRAINT MODEL

被引：4

作者：

Li XiaoguangLam KinManShen Lansun Signal and Information Processing LaboratoryBeijing University of Technology Beijing China Centre for Multimedia Signal ProcessingDepartment of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHong KongChina ^{[100022
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机构：

来源：

Journal of Electronics(China) | 2008年 / 04期

关键词：

Image magnification; Super resolution; Anisotropic diffusion; Gradient-Vector Flow;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

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.

引用

页码：568 / 571

页数：4