Cepstral analysis based blind deconvolution for motion blur

Haruka Asai, Yuji Oyamada, Julien Pilet, Hideo Saito

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

13 Citations (Scopus)

Abstract

Camera shake during exposure blurs the captured image. Despite several decades of studies, image deconvolution to restore a blurred image still remains an issue, particularly in blind deconvolution cases in which the actual shape of the blur is unknown. Approaches based on cepstral analysis succeeded in restoring images degraded by a uniform blur caused by a camera moving straight in a single direction. In this paper, we propose to estimate, from a single blurred image, the point spread function (PSF) caused by a normal camera undergoing a 2D curved motion, and to restore the image. To extend the traditional cepstral analysis, we derive assumptions about the PSF effects in the cepstrum domain. In a first phase, we estimate several PSF candidates from the cepstrum of a blurred image and restore the image with a fast deconvolution algorithm. In a second phase, we select the best PSF candidate by evaluating the restored images. Finally, a slower but more accurate deconvolution algorithm recovers the latent image with the chosen PSF. We validate the proposed method with synthetic and real experiments.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages1153-1156
Number of pages4
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 2010 Sep 262010 Sep 29

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period10/9/2610/9/29

Keywords

  • Blind deconvolution
  • Cepstral analysis
  • Image restoration
  • Point spread function

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Asai, H., Oyamada, Y., Pilet, J., & Saito, H. (2010). Cepstral analysis based blind deconvolution for motion blur. In 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings (pp. 1153-1156). [5651299] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2010.5651299