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

61 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

Keywords

  • Blur measure
  • Edge analysis
  • Image contrast calculation

ASJC Scopus subject areas

  • Engineering(all)

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