抑制寄生波纹的红外图像降晰函数辨识算法

李俊山; 樊景博; 杨亚威; 孙胜永; 任鑫博

doi:10.3788/OPE.20152312.3456

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抑制寄生波纹的红外图像降晰函数辨识算法

信息科学 | 更新时间：2020-08-13

- 抑制寄生波纹的红外图像降晰函数辨识算法
- Blur identification algorithm to suppress parasitic ripples on infrared images
- 光学精密工程 2015年23卷第12期页码：3456-3464
- 作者机构：
  
  1. 第二炮兵工程大学信息工程系,陕西西安,710025
  2. 商洛学院经济与管理学院,陕西商洛,726000
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.61175120)()
- DOI：10.3788/OPE.20152312.3456
  中图分类号： TN216;TP391
- 修回日期：2015-09-14，
  
  纸质出版日期：2015-12-25
- 稿件说明：
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李俊山, 樊景博, 杨亚威等. 抑制寄生波纹的红外图像降晰函数辨识算法[J]. 光学精密工程, 2015,23(12): 3456-3464

LI Jun-shan, FAN Jing-bo, YANG Ya-wei etc. Blur identification algorithm to suppress parasitic ripples on infrared images[J]. Editorial Office of Optics and Precision Engineering, 2015,23(12): 3456-3464
李俊山, 樊景博, 杨亚威等. 抑制寄生波纹的红外图像降晰函数辨识算法[J]. 光学精密工程, 2015,23(12): 3456-3464 DOI： 10.3788/OPE.20152312.3456.

LI Jun-shan, FAN Jing-bo, YANG Ya-wei etc. Blur identification algorithm to suppress parasitic ripples on infrared images[J]. Editorial Office of Optics and Precision Engineering, 2015,23(12): 3456-3464 DOI： 10.3788/OPE.20152312.3456.

摘要

提出了一种针对军事目标红外模糊图像复原的降晰函数辨识算法。该算法根据气动光学效应形成湍流流场的机理建立相应的模型

将点扩展函数简化为可用参数描述的高斯函数形式;利用红外图像的边缘梯度变化特性提出边缘清晰度改善量

并作为降晰函数参数辨识的评价标准

清晰度改善量取最大值时对应的参数就是观测图像的最佳降晰函数参数;针对复原过程中可能出现的振铃效应

运用细节规整化思想衍生的加权空间复原算法

自适应地抑制寄生波纹的产生。实验验证表明

本文方法能有效地复原红外模糊图像

且对降晰函数的辨识准确率高

相对误差可以降低至4.5%左右。另外

抑制振铃寄生波纹效果良好。复原后图像在各项质量评价指标上都有很大提高

峰值信噪比提高量超过9.4 dB

综合评价指数ImageQ提高了20以上。

Abstract

A blur identification algorithm for infrared fuzzy image restoration in military targets was proposed. An appropriate model was established based on the formation mechanism of an aero-optical turbulent field. The point spread function was simplified to a Gaussian function form that could be described by parameters. On the basis of infrared images' edge gradient characteristics

the edge definition improvement was proposed to estimate the blurring parameters and to be acted as the standard of blur identification . When definition improvement was taken its maximum

the corresponding blurring parameter was the optimum parameter of an observation image. For the ringing effects occurred in restoration processing

weighted space restoration algorithm derived from detail regularization was used to adaptively suppress the parasitic ripple. Experimental results show that the algorithm effectively recovers infrared blur images

accurately identifyies the blurring function and the relative errors have reduced to 4.5%.Moreover

the algorithm suppresses perfectly ringing effects during the image restoration process. Data show that all the quality evaluation indicators have been improved

the Peak Signal to Noise Ratio has improved by 9.4 dB and the comprehensive evaluation index ImgeQ improved more than 20.

关键词

Keywords

references

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