吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (4): 1360-1366.doi: 10.13229/j.cnki.jdxbgxb201504048

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Maximum likelihood image restoration combined with image denoising

JIANG Chao1, GENG Ze-xun1, LIU Li-yong2, PAN Ying-feng3   

  1. 1.PLA Information Engineering University, Zhengzhou 450052, China;
    2.National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012;
    3.Troops 61175 of PLA, Nanjing 210049, China
  • Received:2014-03-24 Online:2015-07-01 Published:2015-07-01

Abstract: In the maximum likelihood algorithm proposed by Benvenuto base on mixed noise model, the noise effect during iteration is not taken into consideration and the Point Spread Function (PSF) is assumed to be known and unchanged. This leads to the unstability of the image restoration. Under the condition of noise existence and PSF unknown, an image denoising algorithm is proposed as preprocessing, and the parameter estimation of PSF is introduced into iteration of the maximum likelihood and is dynamically updated. Finally, the Wiener filter with estimated PSF is utilized to improve the quality of the restored image. Experiment result demonstrate that the quality of the restored image is obviously improved, which proves the stability and noise resistance of the proposed algorithm.

Key words: photogrammetry and remote sensing technology, image restoration, mixed noise model, image denoising, point spread function, maximum likelihood

CLC Number: 

  • TP751
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