旋转运动模糊的实时恢复

李仕; 张葆; 孙辉

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旋转运动模糊的实时恢复

信息科学 | 更新时间：2020-08-12

- 旋转运动模糊的实时恢复
- Real-time restoration of images blurred by rotational motion
- 光学精密工程 2009年17卷第3期页码：648-654
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
  
  国防科技预研基金资助项目(No.1040603)()
- DOI：
  中图分类号： TP301.6;TP391.4
- 收稿日期：2008-06-10，
  
  修回日期：2008-06-30，
  
  网络出版日期：2009-03-25，
  
  纸质出版日期：2009-03-25
- 稿件说明：
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李仕, 张葆, 孙辉. 旋转运动模糊的实时恢复[J]. 光学精密工程, 2009,17(3): 648-654

LI Shi, ZHANG Bao, SUN Hui. Real-time restoration of images blurred by rotational motion[J]. Editorial Office of Optics and Precision Engineering, 2009,17(3): 648-654
李仕, 张葆, 孙辉. 旋转运动模糊的实时恢复[J]. 光学精密工程, 2009,17(3): 648-654 DOI：

LI Shi, ZHANG Bao, SUN Hui. Real-time restoration of images blurred by rotational motion[J]. Editorial Office of Optics and Precision Engineering, 2009,17(3): 648-654 DOI：

摘要

提出了一种旋转运动模糊恢复算法

用来解决航空成像时旋转运动模糊的实时恢复问题。对旋转运动模糊这种具有异速像移的空间变化模糊进行了分析

并推导出旋转运动模糊的数学模型。用基于Bresenham画圆法的坐标转换方法将旋转圆弧上的空间变化模糊转变为常见的线性空间不变模糊

并使用一维维纳滤波对圆弧轨迹上的像素点进行模糊恢复。实验结果显示:本文算法在GPU处理平台下用3.31 ms即能恢复一帧1 0241 024

8 bit旋转运动模糊图像

且极好地恢复了图像上的细节信息

恢复图像的峰值信噪比(PSNR)为28.76。算法的速度及效果表明本文所提出的算法具有较大的实用价值。

Abstract

A real-time image restoration algorithm is proposed for the images blurred by rotational motion during aerial imaging.According to the rotational motion with space-variant blur and different motion rates for image

this paper analyzes how the rotational motion is generated and derives a mathematical model of rotational motion.Then

the coordinate conversion based on Bresenham algorithm is applied to transform the space-variant blur on circular arc into the space-invariant blur on pixel lines and 1D Wiener filter is used to restore the linear image motion transformed by coordinate conversion. The experimental results show that the proposed algorithm can restore a 10241024

8 bit blurred image in 3.31 ms on the Graphics Processing Unit (GPU) platform

and the details in the rotational motion blurred image is pretty well restored and the PSNR of the restoration image can reach 28.76. The restoration quality and the effectiveness of the proposed algorithm reveals it is pratical in the aerial imaging system.

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Keywords

references

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