An improved perception-based no-reference objective image sharpness metric using iterative edge refinement

Srenivas Varadarajan, Lina Karam

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

57 Scopus citations

Abstract

The computation of existing sharpness/blurriness objective metrics involves measuring the spread of edge pixels in blurred images. However, in blurred images, many edges might go undetected causing the metrics to become inaccurate. In these scenarios, proper recovery of edge pixels can lead to a better correlation between the perceived sharpness and the sharpness metric. This paper presents an iterative edge refinement algorithm. The proposed edge refinement scheme is integrated into a perceptual-based no-reference sharpness metric resulting in an increased correlation with the perceived sharpness and, thus, in an increased sharpness/blurriness prediction accuracy. Results are presented to illustrate the performance of the proposed scheme and metric.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages401-404
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: Oct 12 2008Oct 15 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2008 IEEE International Conference on Image Processing, ICIP 2008
Country/TerritoryUnited States
CitySan Diego, CA
Period10/12/0810/15/08

Keywords

  • Edge detection
  • HVS
  • Image quality
  • Objective
  • Perception
  • Sharpness metric

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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