A no-reference objective image sharpness metric based on just-noticeable blur and probability summation

Rony Ferzli, Lina Karam

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

33 Scopus citations

Abstract

This work presents a perceptual-based no-reference objective image sharpness/blurriness metric by integrating the concept of Just Noticeable Blur (JNB) into a probability summation model. Unlike existing objective no-reference image sharpness/blurriness metrics, the proposed metric is able to predict the relative amount of blurriness in images with different content. Results are provided to illustrate the performance of the proposed perceptual-based sharpness metric. These results show that the proposed sharpness metric correlates well with the perceived sharpness.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings
PagesIII445-III448
DOIs
StatePublished - Dec 1 2006
Event14th IEEE International Conference on Image Processing, ICIP 2007 - San Antonio, TX, United States
Duration: Sep 16 2007Sep 19 2007

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume3
ISSN (Print)1522-4880

Other

Other14th IEEE International Conference on Image Processing, ICIP 2007
CountryUnited States
CitySan Antonio, TX
Period9/16/079/19/07

Keywords

  • HVS
  • Image assessment
  • Image quality
  • No-reference
  • Objective
  • Perception
  • Sharpness metric

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Ferzli, R., & Karam, L. (2006). A no-reference objective image sharpness metric based on just-noticeable blur and probability summation. In 2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings (pp. III445-III448). [4379342] (Proceedings - International Conference on Image Processing, ICIP; Vol. 3). https://doi.org/10.1109/ICIP.2007.4379342