摘要
提出了一种快速自然运动模糊图像恢复算法,采用一种新的基于Radon变换算法来确定模糊核函数;在确定模糊核函数后,对于模糊图像的恢复采用了一种改进的基于l1范数和l2范数混合保真项的变分图像恢复算法。实验结果表明,与Fergus的算法和Levinss的算法比较,所提算法对于一类线性运动占主要因素的强噪声模糊图像的恢复具有更快的速度和良好的恢复效果。
In this paper, a fast blind restoration algorithm for motion blurred image was proposed, using a robust algorithm based on Radon transform-domain to determine the blur kernel function, then a modified total variation algorithm was used to restore the blurred images. Its cost function is the sum of three terms corresponding to total variation 12-norm regularization, least squares fidelity term and l1-norm fidelity term. Compared with Fergus＇ and Levin＇ algorithm, the experiment results show that the algorithm for a class of motion blurred image caused by the linear movement parallel to the lens has higher speed and good recovery effect.
出处
《计算机应用》
CSCD
北大核心
2014年第7期2005-2009,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(91220301
61175064)
湖南省教育厅一般科研项目(14C0244)
关键词
去卷积
运动模糊
保真项
全变分
deconvolution
motion blur
data fidelity term
total variation
