A non-parametric blur measure based on edge analysis for image processing applications

Yun Chung Chung, Jung Ming Wang, Robert R. Bailey, Sei-Wang Chen, Shyang Lih Chang

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

60 Citations (Scopus)

Abstract

A non-parametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining die standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also Included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.

Original languageEnglish
Title of host publication2004 IEEE Conference on Cybernetics and Intelligent Systems
Pages356-360
Number of pages5
Publication statusPublished - 2004 Dec 1
Event2004 IEEE Conference on Cybernetics and Intelligent Systems - , Singapore
Duration: 2004 Dec 12004 Dec 3

Publication series

Name2004 IEEE Conference on Cybernetics and Intelligent Systems

Other

Other2004 IEEE Conference on Cybernetics and Intelligent Systems
CountrySingapore
Period04/12/104/12/3

Fingerprint

Image processing
Experiments

Keywords

  • Blur measure
  • Edge analysis
  • Image contrast calculation

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Chung, Y. C., Wang, J. M., Bailey, R. R., Chen, S-W., & Chang, S. L. (2004). A non-parametric blur measure based on edge analysis for image processing applications. In 2004 IEEE Conference on Cybernetics and Intelligent Systems (pp. 356-360). (2004 IEEE Conference on Cybernetics and Intelligent Systems).

A non-parametric blur measure based on edge analysis for image processing applications. / Chung, Yun Chung; Wang, Jung Ming; Bailey, Robert R.; Chen, Sei-Wang; Chang, Shyang Lih.

2004 IEEE Conference on Cybernetics and Intelligent Systems. 2004. p. 356-360 (2004 IEEE Conference on Cybernetics and Intelligent Systems).

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

Chung, YC, Wang, JM, Bailey, RR, Chen, S-W & Chang, SL 2004, A non-parametric blur measure based on edge analysis for image processing applications. in 2004 IEEE Conference on Cybernetics and Intelligent Systems. 2004 IEEE Conference on Cybernetics and Intelligent Systems, pp. 356-360, 2004 IEEE Conference on Cybernetics and Intelligent Systems, Singapore, 04/12/1.
Chung YC, Wang JM, Bailey RR, Chen S-W, Chang SL. A non-parametric blur measure based on edge analysis for image processing applications. In 2004 IEEE Conference on Cybernetics and Intelligent Systems. 2004. p. 356-360. (2004 IEEE Conference on Cybernetics and Intelligent Systems).
Chung, Yun Chung ; Wang, Jung Ming ; Bailey, Robert R. ; Chen, Sei-Wang ; Chang, Shyang Lih. / A non-parametric blur measure based on edge analysis for image processing applications. 2004 IEEE Conference on Cybernetics and Intelligent Systems. 2004. pp. 356-360 (2004 IEEE Conference on Cybernetics and Intelligent Systems).
@inproceedings{1609c410865a49e7a3db67440b29a0d3,
title = "A non-parametric blur measure based on edge analysis for image processing applications",
abstract = "A non-parametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining die standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also Included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.",
keywords = "Blur measure, Edge analysis, Image contrast calculation",
author = "Chung, {Yun Chung} and Wang, {Jung Ming} and Bailey, {Robert R.} and Sei-Wang Chen and Chang, {Shyang Lih}",
year = "2004",
month = "12",
day = "1",
language = "English",
isbn = "0780386442",
series = "2004 IEEE Conference on Cybernetics and Intelligent Systems",
pages = "356--360",
booktitle = "2004 IEEE Conference on Cybernetics and Intelligent Systems",

}

TY - GEN

T1 - A non-parametric blur measure based on edge analysis for image processing applications

AU - Chung, Yun Chung

AU - Wang, Jung Ming

AU - Bailey, Robert R.

AU - Chen, Sei-Wang

AU - Chang, Shyang Lih

PY - 2004/12/1

Y1 - 2004/12/1

N2 - A non-parametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining die standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also Included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.

AB - A non-parametric image blur measure is presented. The measure is based on edge analysis and is suitable for various image processing applications. The proposed measure for any edge point is obtained by combining die standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also Included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments on natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image processing applications.

KW - Blur measure

KW - Edge analysis

KW - Image contrast calculation

UR - http://www.scopus.com/inward/record.url?scp=11244312047&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11244312047&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:11244312047

SN - 0780386442

SN - 9780780386440

T3 - 2004 IEEE Conference on Cybernetics and Intelligent Systems

SP - 356

EP - 360

BT - 2004 IEEE Conference on Cybernetics and Intelligent Systems

ER -