Blind restoration of single-channel image using iterative PCA

Ryotaro Nakamura, Yasue Mitsukura, Nozomu Hamada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a single-channel image blind restoration by using iterative principal components analysis (PCA). Previously we proposed the iterative PCA approaches for blind restoration and proved its superiority over conventional methods. Still, there are some problems to be solved. One of them is precise and automatic way to determine the iteration number. This study tries to solve this by applying a blind image quality assessment for automatic optimization of the iterative number. For a verification example of atmospheric turbulence-degraded imagery our proposed method provides better improved restoration quality than conventional methods. In addition, experiments of simulations are conducted for real images. From the results, we can confirm that the proposed method gives higher PSNR as well as SSIM than the conventional methods even in real environments.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE Conference on Systems, Process and Control, ICSPC 2013
PublisherIEEE Computer Society
Pages84-87
Number of pages4
ISBN (Print)9781479922093
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 IEEE Conference on Systems, Process and Control, ICSPC 2013 - Kuala Lumpur, Malaysia
Duration: 2013 Dec 132013 Dec 15

Publication series

NameProceedings - 2013 IEEE Conference on Systems, Process and Control, ICSPC 2013

Other

Other2013 IEEE Conference on Systems, Process and Control, ICSPC 2013
CountryMalaysia
CityKuala Lumpur
Period13/12/1313/12/15

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Keywords

  • atmospheric turbulence
  • blind image qualtity assesment
  • principal components analysis(PCA)
  • shift-invariant
  • single-channel blind image deconvolution

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Nakamura, R., Mitsukura, Y., & Hamada, N. (2013). Blind restoration of single-channel image using iterative PCA. In Proceedings - 2013 IEEE Conference on Systems, Process and Control, ICSPC 2013 (pp. 84-87). [6735108] (Proceedings - 2013 IEEE Conference on Systems, Process and Control, ICSPC 2013). IEEE Computer Society. https://doi.org/10.1109/SPC.2013.6735108