CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
陈曦; 汪彦刚; 彭思龙; ChenXi; WangYangang; PengSilong,; 陈 曦
Source Publication计算机辅助设计与图形学学报,
Volume22(2) (EI)Issue:2010年02期Pages:272-278
Other AbstractDue to t he complicacy of environment , digital images may be degraded by various blurs. An image restoration met hod for t he degradation model is p roposed in t his paper . Unlike t raditional approaches , we assume t hat t he blur kernel is t he mixt ure of defocus and motion blurs. Given the defocus blur , the statistical characteristic of the motion blur is exploited by using generalized Laplacian model , and t hen t he mixed blur is identified using t he expectation maximization ( EM) algorit hm. Finally t he degraded image can be restored based on the estimated blur . Experimental result s demonst rate t hat the p roposed met hod could identify t he blur effectively , and improve visual quality of t he degraded images.
Keyword图像复原 / 运动模糊 / 散焦模糊 / em算法
Document Type期刊论文
Corresponding Author陈 曦
Recommended Citation
GB/T 7714
陈曦,汪彦刚,彭思龙,等. 部分模糊核已知的混合模糊图像复原算法[J]. 计算机辅助设计与图形学学报,,2010,22(2) (EI)(2010年02期):272-278.
APA 陈曦.,汪彦刚.,彭思龙.,ChenXi.,WangYangang.,...&陈 曦.(2010).部分模糊核已知的混合模糊图像复原算法.计算机辅助设计与图形学学报,,22(2) (EI)(2010年02期),272-278.
MLA 陈曦,et al."部分模糊核已知的混合模糊图像复原算法".计算机辅助设计与图形学学报, 22(2) (EI).2010年02期(2010):272-278.
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