Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes

S. Alireza Golestaneh, Lina Karam

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

11 Citations (Scopus)

Abstract

The detection of spatially-varying blur without having any information about the blur type is a challenging task. In this paper, we propose a novel effective approach to address this blur detection problem from a single image without requiring any knowledge about the blur type, level, or camera settings. Our approach computes blur detection maps based on a novel High-frequency multiscale Fusion and Sort Transform (HiFST) of gradient magnitudes. The evaluations of the proposed approach on a diverse set of blurry images with different blur types, levels, and contents demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods qualitatively and quantitatively.

Original languageEnglish (US)
Title of host publicationProceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages596-605
Number of pages10
Volume2017-January
ISBN (Electronic)9781538604571
DOIs
StatePublished - Nov 6 2017
Event30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 - Honolulu, United States
Duration: Jul 21 2017Jul 26 2017

Other

Other30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
CountryUnited States
CityHonolulu
Period7/21/177/26/17

Fingerprint

Fusion reactions
Cameras
Mathematical transformations

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition

Cite this

Alireza Golestaneh, S., & Karam, L. (2017). Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 (Vol. 2017-January, pp. 596-605). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CVPR.2017.71

Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes. / Alireza Golestaneh, S.; Karam, Lina.

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 596-605.

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

Alireza Golestaneh, S & Karam, L 2017, Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes. in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 596-605, 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, United States, 7/21/17. https://doi.org/10.1109/CVPR.2017.71
Alireza Golestaneh S, Karam L. Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 596-605 https://doi.org/10.1109/CVPR.2017.71
Alireza Golestaneh, S. ; Karam, Lina. / Spatially-varying blur detection based on multiscale fused and sorted transform coefficients of gradient magnitudes. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 596-605
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