Wavelet transform based Gaussian point spread function estimation

Qing Chuan Tao*, Hong Bin Deng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

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. 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 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.

Original languageEnglish
Pages (from-to)284-288
Number of pages5
JournalGuangxue Jishu/Optical Technique
Volume30
Issue number3
Publication statusPublished - May 2004

Keywords

  • Gaussian point spread function
  • Lipschitz exponent
  • Maxima of the modulus

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