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Wavelet Transform Based Gaussian Point Spread Function Estimation

  • Qing-Chuan Tao
  • Xiao-Hai He
  • Hong-Bin Deng
  • Ying Liu
  • Jia Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3804)

Abstract

Point spread function (PSF) estimation, an essential part for image restoration, has no accurate estimation algorithm at present. Based on the wavelet theory, a new Gaussian PSF accurate estimation algorithm is put forward in this paper. Firstly, the blurred images are smoothed, and their noise is reduced. Secondly, wavelet with varied scales is transformed, after which the local maxima of the modulus of the wavelet are computed respectively. Thirdly, on the basis of the relation deduced in this paper among the local maxima of the modulus of the wavelet at different scales, Lipschitz exponent and variance, the variance of a Gaussian PSF is computed. The experimental result shows that the proposed algorithm has an accuracy rate as high as 95%, and is of great application value.

Keywords

Gaussian Function Point Spread Function Wavelet Function Image Restoration Edge Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Qing-Chuan Tao
    • 1
  • Xiao-Hai He
    • 1
  • Hong-Bin Deng
    • 2
  • Ying Liu
    • 1
  • Jia Zhao
    • 1
  1. 1.College of Electronic InformationSichuan UniversityChengduP.R. China
  2. 2.School of Information EngineeringBeijing Institute of TechnologyBeijingP.R. China

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