• Laser & Optoelectronics Progress
  • Vol. 60, Issue 4, 0428003 (2023)
Qiyao Wang1、1、3、3、">">, Zhuoyue Hu1、*, Xiaoyan Li1、1、2、2、">">, and Fansheng Chen1、1、2、2、">">
Author Affiliations
  • 1Key Laboratory of Intelligent Infrared Perception, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
  • 2Hangzhou Institute for Advanced Study, National University of Defense Technology, Zhejiang 310024, Hangzhou, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    DOI: 10.3788/LOP212682 Cite this Article Set citation alerts
    Qiyao Wang, Zhuoyue Hu, Xiaoyan Li, Fansheng Chen. Blind Deblurring of Remote Sensing Images Based on Local Maximum and Minimum Intensity Priors[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0428003 Copy Citation Text show less

    Abstract

    A blind deblurring method of remote sensing images based on local maximum and minimum intensity priors is proposed to solve the motion blur problem. The sparsity of local pixel intensity of remote sensing image is used as a prior condition in this method, and a simple iterative threshold shrinkage method is applied to solve the latent image and blur kernel, then we obtain the deblurred image using by non-blind deconvolution algorithm. The experimental results show that the proposed method can improve the computational efficiency. For both optical and near-infrared remote sensing images, it can availably restore the texture details of the images, suppress artifacts, and improve the subjective effect and objective evaluation index for the restored images.
    Qiyao Wang, Zhuoyue Hu, Xiaoyan Li, Fansheng Chen. Blind Deblurring of Remote Sensing Images Based on Local Maximum and Minimum Intensity Priors[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0428003
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