摘要
图像复原是数字图像处理的一个重要课题,而运动模糊图像复原在图像复原中占有重要地位。本文首先介绍了图像退化模型,其次又描述了逆滤波和维纳滤波两种经典复原算法的基本原理和其复原过程,然后利用Matlab对有噪声和无噪声两种情况下的运动模糊图像采用上述两种经典方法进行仿真实验,实验结果表明,在有噪声和无噪声的两种情况下,逆滤波和维纳滤波各有优劣。最后又提出将维纳滤波与均值滤波相结合的组合滤波复原技术,该方法先弱化噪声后复原图像,从而达到更好的图像复原效果。
Image restoration is an important subject of digital image processing, and motion blurred image restoration plays an important role in image restoration. This article first introduces the image degradation model, and then describes the basic principles and their restoration processes of two classic restoration algorithms, inverse filtering and Wiener filtering, and then uses Matlab to apply the above to motionblurred images with and without noise. Two classical methods are used for simulation experiments. The experimental results show that inverse noise filtering and Wiener filtering have their own advantages and disadvantages in the two cases with and without noise. Finally, a combination filtering restoration technique combining Wiener filtering and mean filtering is proposed. This method first weakens the noise and then restores the image, so as to achieve a better image restoration effect.
作者
王建新
黄培
WANG Jian-xin;HUANG Pei
出处
《信息技术与信息化》
2019年第12期95-98,共4页
Information Technology and Informatization
关键词
图像退化模型
图像复原算法
组合维纳滤波
Image degradation model
image restoration algorithm
combined Wiener filtering
