Efficient full-reference assessment of image and video quality

  • Patrick Ndjiki-Nya*
  • , Mikel Barrado
  • , Thomas Wiegand
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

Automatic quality assessment of digital pictures is a crucial issue in several image and video processing applications including broadcasting, archiving, or restoration. The visibility of impairments related to digital image processing systems is subject to the spatio-temporal properties of the given image or video content. As quality assessment using subjective tests carried out by humans is very costly, time consuming, and not compatible with real-time constraints, objective measures are required that can predict the perceptual judgment of human viewers. In this paper, a top-down quality assessment tool that mimics a selection of prominent human visual system properties is presented. Quality evaluation is conducted based on perceptually salient feature points in our approach. It is shown that the proposed method, although featuring a significantly lower complexity than standardized quality measures, performs as well as these for block-based hybrid video coding.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings
PagesII125-II128
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event14th IEEE International Conference on Image Processing, ICIP 2007 - San Antonio, TX, United States
Duration: 16 Sept 200719 Sept 2007

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2
ISSN (Print)1522-4880

Conference

Conference14th IEEE International Conference on Image Processing, ICIP 2007
Country/TerritoryUnited States
CitySan Antonio, TX
Period16/09/0719/09/07

Keywords

  • Block transform coding
  • Image
  • Quality assessment
  • Video

Fingerprint

Dive into the research topics of 'Efficient full-reference assessment of image and video quality'. Together they form a unique fingerprint.

Cite this