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
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
  • [31] Blind restoration of turbulence degraded images based on two-channel alternating minimization algorithm
    Yang Huizhen
    Li Songheng
    Li Xin
    Zhang Zhiguang
    Yang Haibo
    Liu Jinlong
    OPTOELECTRONICS LETTERS, 2022, 18 (02) : 122 - 128
  • [32] 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
  • [33] Blind restoration of turbulence degraded images based on two-channel alternating minimization algorithm
    Huizhen Yang
    Songheng Li
    Xin Li
    Zhiguang Zhang
    Haibo Yang
    Jinlong Liu
    Optoelectronics Letters, 2022, 18 : 122 - 128
  • [34] Image Restoration Algorithm Based on Double l0-Regularization and ALM
    Xiao, Su
    ENGINEERING LETTERS, 2023, 31 (01) : 19 - 19
  • [35] Phase retrieval algorithm for turbulence-degraded image based on fractional Fourier transform
    Cao, Dong
    Jin, Gang
    An, Tao
    Liu, Lin-Yan
    Kongqi Donglixue Xuebao/Acta Aerodynamica Sinica, 2010, 28 (04): : 381 - 384
  • [36] Urban Night Image Restoration Algorithm Based on Space Model
    Hu Jing
    Liu Yuanyuan
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, : 230 - 235
  • [37] Research on Restoration Algorithm of Two-dimensional Degraded Image Based on Deep Learning
    Jin, Jing
    Wang, Keyi
    Wang, Wei
    PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020), 2020, : 1144 - 1148
  • [38] Identification and restoration of the turbulence degraded images based on the parametric estimation
    Li Dongxing
    Zhao Yan
    Xu Dong
    ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS, 2007, : 1575 - 1578
  • [39] Restoration of Atmospheric Turbulence-Degraded Short-Exposure Image Based on Convolution Neural Network
    Cheng, Jiuming
    Zhu, Wenyue
    Li, Jianyu
    Xu, Gang
    Chen, Xiaowei
    Yao, Cao
    PHOTONICS, 2023, 10 (06)
  • [40] Blind Restoration of a Single Real Turbulence-Degraded Image Based on Self-Supervised Learning
    Guo, Yiming
    Wu, Xiaoqing
    Qing, Chun
    Liu, Liyong
    Yang, Qike
    Hu, Xiaodan
    Qian, Xianmei
    Shao, Shiyong
    REMOTE SENSING, 2023, 15 (16)