Defocus Map Detection Using a Single Image

Juan Andrade

doi:10.1109/CSCI.2016.0151

Defocus Map Detection Using a Single Image

Juan Andrade

Arizona State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The estimation of blurred regions is an important stage in several computer vision applications. In this paper an efficient training-free detector of local blurriness based on edge features is presented. Due to the intrinsic sparsity of edges in natural images a blur map is creating by using an approach based on the heat diffusion principle. A 2D point discrete Poisson solver is concatenated with a guided filter stage in order to create the blurring map. Experiments with images from two publicly available datasets validate the proposed method.

Original language	English
Title of host publication	Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
Editors	Mary Yang, Hamid R. Arabnia, Leonidas Deligiannidis, Leonidas Deligiannidis
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	777-780
Number of pages	4
ISBN (Electronic)	9781509055104
DOIs	https://doi.org/10.1109/CSCI.2016.0151
State	Published - 17 Mar 2017
Externally published	Yes
Event	2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 - Las Vegas, United States Duration: 15 Dec 2016 → 17 Dec 2016

Publication series

Name	Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

Conference

Conference	2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
Country/Territory	United States
City	Las Vegas
Period	15/12/16 → 17/12/16

Keywords

blur map
out of focus
Poisson solver

Access to Document

10.1109/CSCI.2016.0151

Cite this

Andrade, J. (2017). Defocus Map Detection Using a Single Image. In M. Yang, H. R. Arabnia, L. Deligiannidis, & L. Deligiannidis (Eds.), Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 (pp. 777-780). Article 7881444 (Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI.2016.0151

Andrade, Juan. / Defocus Map Detection Using a Single Image. Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016. editor / Mary Yang ; Hamid R. Arabnia ; Leonidas Deligiannidis ; Leonidas Deligiannidis. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 777-780 (Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016).

@inproceedings{ab31a9e0817e4ba2a7dac3b04ed9e7a0,

title = "Defocus Map Detection Using a Single Image",

abstract = "The estimation of blurred regions is an important stage in several computer vision applications. In this paper an efficient training-free detector of local blurriness based on edge features is presented. Due to the intrinsic sparsity of edges in natural images a blur map is creating by using an approach based on the heat diffusion principle. A 2D point discrete Poisson solver is concatenated with a guided filter stage in order to create the blurring map. Experiments with images from two publicly available datasets validate the proposed method.",

keywords = "blur map, out of focus, Poisson solver",

author = "Juan Andrade",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 ; Conference date: 15-12-2016 Through 17-12-2016",

year = "2017",

month = mar,

day = "17",

doi = "10.1109/CSCI.2016.0151",

language = "Ingl{\'e}s",

series = "Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "777--780",

editor = "Mary Yang and Arabnia, \{Hamid R.\} and Leonidas Deligiannidis and Leonidas Deligiannidis",

booktitle = "Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016",

}

Andrade, J 2017, Defocus Map Detection Using a Single Image. in M Yang, HR Arabnia, L Deligiannidis & L Deligiannidis (eds), Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016., 7881444, Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016, Institute of Electrical and Electronics Engineers Inc., pp. 777-780, 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016, Las Vegas, United States, 15/12/16. https://doi.org/10.1109/CSCI.2016.0151

Defocus Map Detection Using a Single Image. / Andrade, Juan.
Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016. ed. / Mary Yang; Hamid R. Arabnia; Leonidas Deligiannidis; Leonidas Deligiannidis. Institute of Electrical and Electronics Engineers Inc., 2017. p. 777-780 7881444 (Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Defocus Map Detection Using a Single Image

AU - Andrade, Juan

PY - 2017/3/17

Y1 - 2017/3/17

N2 - The estimation of blurred regions is an important stage in several computer vision applications. In this paper an efficient training-free detector of local blurriness based on edge features is presented. Due to the intrinsic sparsity of edges in natural images a blur map is creating by using an approach based on the heat diffusion principle. A 2D point discrete Poisson solver is concatenated with a guided filter stage in order to create the blurring map. Experiments with images from two publicly available datasets validate the proposed method.

AB - The estimation of blurred regions is an important stage in several computer vision applications. In this paper an efficient training-free detector of local blurriness based on edge features is presented. Due to the intrinsic sparsity of edges in natural images a blur map is creating by using an approach based on the heat diffusion principle. A 2D point discrete Poisson solver is concatenated with a guided filter stage in order to create the blurring map. Experiments with images from two publicly available datasets validate the proposed method.

KW - blur map

KW - out of focus

KW - Poisson solver

UR - https://publicaciones.ucuenca.edu.ec/ojs/index.php/medicina/article/view/3012/2288

U2 - 10.1109/CSCI.2016.0151

DO - 10.1109/CSCI.2016.0151

M3 - Contribución a la conferencia

AN - SCOPUS:85017289320

T3 - Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

SP - 777

EP - 780

BT - Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

A2 - Yang, Mary

A2 - Arabnia, Hamid R.

A2 - Deligiannidis, Leonidas

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

Y2 - 15 December 2016 through 17 December 2016

ER -

Andrade J. Defocus Map Detection Using a Single Image. In Yang M, Arabnia HR, Deligiannidis L, Deligiannidis L, editors, Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 777-780. 7881444. (Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016). doi: 10.1109/CSCI.2016.0151

Defocus Map Detection Using a Single Image

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this