改进的固定点图像复原算法

阎雪飞; 许廷发; 白廷柱

doi:10.3788/CO.20130603.0318

改进的固定点图像复原算法

doi: 10.3788/CO.20130603.0318

北京理工大学光电学院光电成像技术与系统教育部重点实验室, 北京 100081

基金项目:

Major State Basic Research Development Program of China(973 Program, No.2009CB72400603);The National Natural Science:Scientific Instrumentation Special Project(No.61027002);The National Natural Science Foundation of China(No.60972100)

详细信息

通讯作者:
许廷发

中图分类号: TP391.4
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出版历程
- 收稿日期: 2013-02-11
- 修回日期: 2013-04-13
- 刊出日期: 2013-06-10

Improved fixed point method for image restoration

Key Laboratory of Photoelectric Imaging Technology and System of the Ministry of Education, College of Optical Engineering, Beijing Institute of Technology, Beijing 100081, China

More Information

Author Bio:
YAN Xue-fei(1979-), male, PhD student. He received his B.S. degree in electronics engineering from Shanxi University in 2002, and received his M.S. degree in Optical Engineering from Beijing Institute of Technology in 2007. His research interests include image deblurring. E-mail:yxfamyself@sina.com

摘要

摘要: 研究了周期边界条件下,Tikhonov正则化的固定点算法,提出了变化正则化参数的方法。首先对正则化参数取较大值,抑制复原图像中的噪声,通过得出的收敛结果来修正初始梯度;然后对正则化参数取较小值,以增强复原图像中的细节。实验结果表明,与当前求解L1范数正则化函数和全变分正则化函数的流行算法比较,本文算法对于运动模糊与高斯模糊图像的复原效果更佳。
- 图像复原 /
- 周期边界条件 /
- Tikhonov正则化 /
- 变正则化参数
Abstract: We analyze the fixed point method with Tikhonov regularization under the periodic boundary conditions, and propose a changable regularization parameter method. Firstly, we choose a bigger one to restrain the noise in the reconstructed image, and get a convergent result to modify the initial gradient. Secondly, we choose a smaller one to increase the details in the image. Experimental results show that compared with other popular algorithms which solve the L1 norm regularization function and Total Variation(TV) regularization function, the improved fixed point method performs favorably in solving the problem of the motion degradation and Gaussian degradation.
- image restoration /
- periodic boundary condition /
- Tikhonov regularization /
- change regularization parameter

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