Blur identification algorithm to suppress parasitic ripples on infrared images

LI Jun-shan; FAN Jing-bo; YANG Ya-wei; SUN Sheng-yong; REN Xin-bo

doi:10.3788/OPE.20152312.3456

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Blur identification algorithm to suppress parasitic ripples on infrared images

Information Sciences | 更新时间：2020-08-13

- Blur identification algorithm to suppress parasitic ripples on infrared images
- Optics and Precision Engineering Vol. 23, Issue 12, Pages: 3456-3464(2015)
- 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：
- DOI：10.3788/OPE.20152312.3456
  CLC： TN216;TP391
- Revised：14 September 2015，
  
  Published：25 December 2015
- 稿件说明：
移动端阅览
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

JUMPER E J,FITZGERALDEJ. Recent advances in aero-optics[J]. Progress in Aerospace Science, 2001, 37: 299-339.

曹东,金钢,安涛,等. 基于分数阶傅立叶变换的湍流退化图像相位恢复算法研究[J]. 空气动力学学报, 2010, 28(4): 381-384. CAO D, JIN G, AN T, et al.. Phase retrieval algorithm for turbulence-degraded image based on fractional Fourier transform [J]. Acta Aerodynamica Sinica, 2010, 28(4): 381-384. (in Chinese)

赵剡,宗云花,张世军,等. 气动光学效应降晰函数辨识与图像复原[J]. 兵工学报,2005,26(2):188-191. ZHAO Y, ZONG Y H, ZHANG SH J, et al.. Identification of blurs for aero-optics effect[J]. Acta ArmamentarⅡ, 2005, 26(2): 188-191. (in Chinese)

赵剡,张春晓. 改进的基于白化滤波器的降晰函数尺寸估计方法[J]. 红外与激光工程,2010, 39(5): 896-901. ZHAO Y, ZHANG CH X. Improved method of blur support size identification based on the whiten filter [J]. Infrared and Laser Engineering, 2010, 39(5): 896-901. (in Chinese)

XU L, JIA J Y. Two-phase kernel estimation for robust motion deblurring[C]. Proceedings of the 11th European Conference on Computer Vision, 2010,6311: 157-170.

孟伟,金龙旭,李国宁,等. 调制传递函数在遥感图像复原中的应用[J]. 红外与激光工程,2014,43(5):1690-1696. MENG W, JIN L X, LI G N, et al.. Application of MTF in remote sensing image restoration[J]. Infrared and Laser Engineering, 2014, 43(5): 1690-1696. (in Chinese)

贤光,颜昌翔,张新洁. 运动模糊图像点扩散函数的频谱估计法[J]. 液晶与显示, 2014,29(5):751-755. XIAN G, YAN CH X, ZHANG X J. Motion-blurred image point spread function estimation method based on spectral analysis[J]. Chinese Journal of Liquid Crystals and Displays, 2014,29(5):751-755. (in Chinese)

张士杰,李俊山,杨亚威,等. 湍流退化红外图像降晰函数辨识[J]. 光学精密工程,2013,21(2):514-521. ZHANG SH J, LI J SH, YANG Y W, et al.. Bluridentificationofturbulence-degradedIRimage[J]. Opt. Precision Eng., 2013,21(2): 514-521. (in Chinese)

CHERNOV L A. Wave Propagation in a Random Medium[M]. New York: McGraw-Hill,1960.

BANISH M, CLARK R L, KATHMAN A. A validated code to predict the performance of onboard broadband optical seekers through a turbulent transonic flow[C]. AIAA ADIO Annual Interceptor Technology Conference, Huntsville, Alabama, 1992.

邹谋炎.反卷积和信号复原[M]. 北京:国防工业出版社,2001. ZOU M Y. Deconvolution and Signal Recovery [M]. Beijing: National Defense Industry Press, 2001.(in Chinese)

程光权,张继东,成礼智,等. 基于几何结构失真模型的图像质量评价研究[J]. 自动化学报, 2011,37(7):811-819. CHENG G Q, ZHANG J D, CHENG L ZH, et al.. Image quality assessment based on geometric structural distortion model [J]. Acta Automatica Sinica, 2011,37(7):811-819. (in Chinese)

葛仕明,程义民,李杰,等. 基于边缘和梯度场的图像表示和压缩方法[J]. 中国科学院研究生院学报,2009,26(2):235-242. GE SH M, CHENG Y M, LI J, et al.. Image representation and compression using edge and gradient field [J]. Journal of the Graduate School of the Chinese Academy of Sciences,2009,26(2):235-242. (in Chinese)

倪军,袁家虎,吴钦章. 基于边缘特征的光学图像清晰度判定[J]. 中光激光,2009,36(1):172-176. NI J, YUAN J H, WU Q ZH. Identification for optical image definition based on edge feature[J]. Chinese Journal of Lasers, 2009,36(1):172-176. (in Chinese)

赵剡,李东兴,许东. 抑制复原图像振铃波纹的频域循环边界算法[J]. 北京航空航天大学学报, 2006, 32(11): 1290-1293. ZHAO Y, LI D X, XU D. Circulation edge algorithm in frequency domain to suppress the ringing ripples on the restored image[J]. Journal of Beijing University of Aeronautics and Astronautics,2006,32(11) :1290-1293. (in Chinese)

FOI A, DABOV K, KATKOVNIK V, et al.. Shape-adaptive DCT for denoising and image reconstruction[C]. Proceedings of SPIE-IS&T Electronic Imaging, 2006, 203-214.

WANG Y L,YANG J F,YIN W T, et al.. A new alternating minimization algorithm for total variation image reconstruction[J]. SIAM Journal on Imaging Sciences, 2008, 1(3): 248-272.

LAGENDIJK R L, BIEMOND J, BOEKEE D E. Regularized iterative image restoration with ringing reduction[J]. IEEE Trans. Acoust. Speech Signal Proc.,1988,36:1874-1888.

GABARDA S, CRISTBAL G. Blind image quality assessment through anisotropy[J]. Journal of the Optical Society of America A-Optics Image Science and Vision,2007, 24(12):42-51.

耿则勋,陈波,王振国,等.自适应光学图像复原理论与方法[M]. 北京:科学出版社,2010. GENG Z X, CHEN B, WANG ZH G, et al.. Adaptive Optics Image Restoration Theory and Method [M]. Beijing: Science Press,2010.(in Chinese)

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Related Institution

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

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