现代电子技术Issue(5)：85-88,4.DOI:10.16652/j.issn.1004-373x.2016.05.020
基于非凸lp范数和G-范数的图像去模糊模型
Image deblurring model base on non-convex lp norm and G-norm
摘要
Abstract
Image deblurring is an important problem in image restoration. For the classical deblurring method,an image de⁃blurring method based on the integration of non⁃convex lp(0p<1) norm and G⁃norm is proposed. The lp(0p<1) norm is taken as the regular term constraint to ensure the sparse feature of the image,and the G⁃norm as the fidelity item can effectively suppress the noise and keep the small feature of image while ensuring the deblurring. The new method based on the effective algorithm of alternating minimization is given. The experimental results show that the new model is feasible.关键词
图像去模糊/lp (0p<1)范数/G范数/交替最小化Key words
image deblurring/lp(0p<1) norm/G-norm/alternating minimization分类
信息技术与安全科学引用本文复制引用
张凯,李敏..基于非凸lp范数和G-范数的图像去模糊模型[J].现代电子技术,2016,(5):85-88,4.基金项目
国家自然科学基金（61472257）；深圳市基础研究项目（JCYJ20120613114019685）；教育部博士点基金 （）
