Efficient perceptual-based spatially varying out-of-focus blur detection

Tong Zhu, Lina Karam

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

3 Citations (Scopus)

Abstract

This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages2673-2677
Number of pages5
Volume2016-August
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

Keywords

  • Blur
  • Blur detection
  • Deblurring
  • HVS
  • Out-of-focus
  • Perception

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Zhu, T., & Karam, L. (2016). Efficient perceptual-based spatially varying out-of-focus blur detection. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (Vol. 2016-August, pp. 2673-2677). [7532844] IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7532844

Efficient perceptual-based spatially varying out-of-focus blur detection. / Zhu, Tong; Karam, Lina.

2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. Vol. 2016-August IEEE Computer Society, 2016. p. 2673-2677 7532844.

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

Zhu, T & Karam, L 2016, Efficient perceptual-based spatially varying out-of-focus blur detection. in 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. vol. 2016-August, 7532844, IEEE Computer Society, pp. 2673-2677, 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, United States, 9/25/16. https://doi.org/10.1109/ICIP.2016.7532844
Zhu T, Karam L. Efficient perceptual-based spatially varying out-of-focus blur detection. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. Vol. 2016-August. IEEE Computer Society. 2016. p. 2673-2677. 7532844 https://doi.org/10.1109/ICIP.2016.7532844
Zhu, Tong ; Karam, Lina. / Efficient perceptual-based spatially varying out-of-focus blur detection. 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. Vol. 2016-August IEEE Computer Society, 2016. pp. 2673-2677
@inproceedings{350ea613b882415b8cb4b206db248e2e,
title = "Efficient perceptual-based spatially varying out-of-focus blur detection",
abstract = "This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.",
keywords = "Blur, Blur detection, Deblurring, HVS, Out-of-focus, Perception",
author = "Tong Zhu and Lina Karam",
year = "2016",
month = "8",
day = "3",
doi = "10.1109/ICIP.2016.7532844",
language = "English (US)",
volume = "2016-August",
pages = "2673--2677",
booktitle = "2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings",
publisher = "IEEE Computer Society",
address = "United States",

}

TY - GEN

T1 - Efficient perceptual-based spatially varying out-of-focus blur detection

AU - Zhu, Tong

AU - Karam, Lina

PY - 2016/8/3

Y1 - 2016/8/3

N2 - This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.

AB - This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.

KW - Blur

KW - Blur detection

KW - Deblurring

KW - HVS

KW - Out-of-focus

KW - Perception

UR - http://www.scopus.com/inward/record.url?scp=85006818087&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006818087&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2016.7532844

DO - 10.1109/ICIP.2016.7532844

M3 - Conference contribution

VL - 2016-August

SP - 2673

EP - 2677

BT - 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings

PB - IEEE Computer Society

ER -