Restoration Algorithm of Heavy Turbulence Degraded Image for Space Target based on Regularization

被引:0
|
作者
Wang Liang-liang [1 ]
Tao Zhi-wei [2 ]
Li Ming [1 ]
Gao Xin [1 ]
机构
[1] Beijing Inst Tracking & Telecommun Technol Beijin, Beijing 100094, Peoples R China
[2] China Aerosp Sci & Technol Corp, Beijing 100048, Peoples R China
来源
INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2011: SPACE EXPLORATION TECHNOLOGIES AND APPLICATIONS | 2011年 / 8196卷
关键词
regularization; image restoration; space target; turbulence-degraded image;
D O I
10.1117/12.899877
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Restoration of atmospheric turbulence-degraded image is needed to be solved as soon as possible in the field of astronomical space technology. This paper discusses the issue of regularization during the restoration process, a new restoration method of heavy turbulence-degrade image for space target based on regularization is proposed, in which the anisotropic, nonlinear Step-like and Gussian-like regularization models are adopted according to the properties of turbulence point spread function(PSF) and image. The nonlinear regularization functions are suggested to smooth in the process of estimating the PSF and recover the object image. In order to test the validity of the method, a series of restoration experiments are performed on the heavy turbulence-degraded images for space target and the experiment results show that the method is effective to restore the space object from their heavy turbulence-degraded images. Besides, the definition measures and relative definition measures show that the new method is better than the traditional method for restoration result.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Compound Algorithm for Restoration of Heavy Turbulence-Degraded Image for Space Target
    Wang, Liang-liang
    Wang, Ru-jie
    Li, Ming
    Kang, Zi-qian
    Xu, Xiao-qin
    Gao, Xin
    OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY II, 2012, 8558
  • [2] An Underwater Turbulence Degraded Image Restoration Algorithm
    Furhad, Md. Hasan
    Tahtali, Murat
    Lambert, Andrew
    UNCONVENTIONAL AND INDIRECT IMAGING, IMAGE RECONSTRUCTION, AND WAVEFRONT SENSING 2017, 2017, 10410
  • [3] Turbulence-Blurred Target Restoration Algorithm with a Nonconvex Regularization Constraint
    Xu, Xinggui
    Hong, Li
    Bing, Ran
    Ren, Weihe
    Song, Junrong
    LASER & OPTOELECTRONICS PROGRESS, 2025, 62 (02)
  • [4] IMAGE ACCELERATION RESTORATION ALGORITHM FOR TURBULENCE-DEGRADED IMAGES BASED ON SUPPORT VECTOR MACHINE
    Li Ming
    Yang Jie
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2009, 28 (06) : 472 - 475
  • [5] Hybrid regularization image restoration algorithm based on total variation
    Zhang, Hongmin
    Wang, Yan
    INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2013: INFRARED IMAGING AND APPLICATIONS, 2013, 8907
  • [6] A novel atmospheric turbulence-degraded image restoration algorithm based on support vector regression
    Liu Chun-Sheng
    Li Ming
    SIGNAL ANALYSIS, MEASUREMENT THEORY, PHOTO-ELECTRONIC TECHNOLOGY, AND ARTIFICIAL INTELLIGENCE, PTS 1 AND 2, 2006, 6357
  • [7] Blind restoration of real turbulence-degraded image with complicated backgrounds using anisotropic regularization
    Hong, Hanyu
    Li, Liangcheng
    Zhang, Tianxu
    OPTICS COMMUNICATIONS, 2012, 285 (24) : 4977 - 4986
  • [8] Restoration algorithm for turbulence-degraded images based on multi-scale blind deconvolution
    Hong, Hanyu
    Zhang, Tianxu
    Yu, Jiuyang
    MIPPR 2007: MULTISPECTRAL IMAGE PROCESSING, 2007, 6787
  • [9] Study on restoration method for turbulence-degraded image based on maximum likelihood
    Xie, Shenghua
    Zhang, Qiheng
    Su, Ding
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 780 - 780
  • [10] CNN-Based Restoration of a Single Face Image Degraded by Atmospheric Turbulence
    Yasarla, Rajeev
    Patel, Vishal M.
    IEEE TRANSACTIONS ON BIOMETRICS, BEHAVIOR, AND IDENTITY SCIENCE, 2022, 4 (02): : 222 - 233