A non-iterative blind image deblurring algorithm based on OTF estimation

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Abstract

This paper proposes a non-iterative algorithm on blind image deblurring. This algorithm can restore the degraded images which are blurred by class G. This algorithm is based on that most images spectral amplitude have the similar power law distribution. In accordance with the power law distribution of natural image spectrum, a curve model is proposed to approximate the spectrum of the true image. The OTF(optical transfer function) is estimated by comparing the spectrum of the degraded image with the reconstructed one. Then, the image is restored by employing the estimated OTF and the Wiener filtering. The experiments show that this algorithm obtains a more accurate OTF, and this algorithm can reduce ringing artifacts as compared with some existing algorithms. The quality of the restored images has been enhanced significantly.

Original languageEnglish
Title of host publication2017 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages628-633
Number of pages6
ISBN (Electronic)9781538621592
DOIs
StatePublished - 2 Jul 2017
Event25th International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2017 - Xiamen, China
Duration: 6 Nov 20179 Nov 2017

Publication series

Name2017 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2017 - Proceedings
Volume2018-January

Conference

Conference25th International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2017
Country/TerritoryChina
CityXiamen
Period6/11/179/11/17

Keywords

  • Atmospheric turbulence
  • Blind image deblurring
  • Lévy processes
  • OTF estimation

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