Total variation image restoration for mixed blur in moving image

SHI Ming-zhu; XU Ting-fa; ZHANG Kun

doi:10.3788/OPE.20111908.1973

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Total variation image restoration for mixed blur in moving image

Article | 更新时间：2020-08-12

- Total variation image restoration for mixed blur in moving image
- Optics and Precision Engineering Vol. 19, Issue 8, Pages: 1973-1981(2011)
- 作者机构：
  
  1. 北京理工大学光电学院,北京 10081
  2. 北京理工大学光电成像技术与系统教育部重点实验室,北京 100081
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111908.1973
  CLC： TP391.4
- Received：09 June 2011，
  
  Revised：01 July 2011，
  
  Published Online：25 August 2011，
  
  Published：25 August 2011
- 稿件说明：
移动端阅览
石明珠, 许廷发, 张坤. 运动成像混合模糊的全变分图像复原[J]. 光学精密工程, 2011,19(8): 1973-1981

SHI Ming-zhu, XU Ting-fa, ZHANG Kun. Total variation image restoration for mixed blur in moving image[J]. Editorial Office of Optics and Precision Engineering, 2011,19(8): 1973-1981
石明珠, 许廷发, 张坤. 运动成像混合模糊的全变分图像复原[J]. 光学精密工程, 2011,19(8): 1973-1981 DOI： 10.3788/OPE.20111908.1973.

SHI Ming-zhu, XU Ting-fa, ZHANG Kun. Total variation image restoration for mixed blur in moving image[J]. Editorial Office of Optics and Precision Engineering, 2011,19(8): 1973-1981 DOI： 10.3788/OPE.20111908.1973.

摘要

为了实现运动成像中视频帧内复原

研究了帧内运动模糊和离焦模糊两种常见模糊类型带来的混合模糊问题。首先

依据模糊图像的频谱特性定性判定模糊类型

利用倒谱分析的方法定量估计模糊模型点扩散函数

依据工程实际选取模糊参数进行仿真实验

实现点扩散函数估计方法的准确性验证。然后

采用耦合梯度保真项的改进型全变分图像复原算法

约束点扩散函数估计误差对图像复原的影响

并采用适应

范数的Split-Bregman算法完成复原算法的数值实现。最后

对算法性能进行验证

完成仿真和实拍混合模糊图像的复原。实验结果表明

倒谱分析估计点扩散函数的准确率达到90%。复原算法能保持图像边缘和细节

并有效抑制振铃效应

帧内稳像的图像峰值信噪比为28.92 dB。

Abstract

In order to restore the image in the video frame of a moving image

the mixed blur that combines two common blur types

motion blur and defocus blur

was discussed. Firstly

blur types were determined according to the difference in spectrum features and the Point Spread Function (PSF) was estimated quantitatively using the cepstrum analysis. Blur parameters in simulation experiments were chosen based on engineering to verify the accuracy of the cepstrum analysis in the PSF estimation method. Then

a gradient fidelity term was coupled with total variation image restoration algorithm to constrain the impact of the PSF estimation error on image restoration and the Split-Bregman algorithm that is compatible with the

norm was adopted to accomplish the numerical computing in restoration algorithm. Finally

the simulation experiments and the real image restoration were carried to verify the performance of the algorithm. The results show that cepstrum analysis for estimating the PSF has an accuracy rate of 90%.The proposed algorithm can preserve edges and details

inhibit the ringing effect effectively and shows its Peak Signal to Noise Rate (PSNR) to be 28.92 dB.

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Keywords

references

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