Full-reference predictive modeling of subjective image quality assessment with ANFIS

El Sayed M. El-Alfy*, Mohammed Rehan Riaz

*Corresponding author for this work

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

Abstract

Digital images often undergo through various processing and distortions which subsequently impacts the perceived image quality. Predicting image quality can be a crucial step to tune certain parameters for designing more effective acquisition, transmission, and storage multimedia systems. With the huge number of images captured and exchanged everyday, automatic prediction of image quality that correlates well with human judgment is steadily gaining increased importance. In this paper, we investigate the performance of three combinations of objective metrics for image quality prediction with an adaptive neuro-fuzzy inference system (ANFIS). Images are processed to extract various attributes which are then used to build a predictive model to estimate a differential mean opinion score for different types of distortions. Using a publicly available and subjectively rated image database, the proposed method is evaluated and compared to individual metrics and an existing technique based on correlation and error measures. The results prove that the proposed method can be a promising approach for predicting subjective quality of images.

Original languageEnglish
Title of host publicationAgents and Artificial Intelligence - 6th International Conference, ICAART 2014, Revised Selected Papers
EditorsJaap van den Herik, Joaquim Filipe, Jaap van den Herik, Béatrice Duval, Stephane Loiseau, Joaquim Filipe, Béatrice Duval, Stephane Loiseau
PublisherSpringer Verlag
Pages296-311
Number of pages16
ISBN (Print)9783319252094, 9783319252094
DOIs
StatePublished - 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8946
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

  • ANFIS
  • Adaptive neuro-fuzzy inference system
  • Differential mean opinion score
  • Human visual system
  • Image quality assessment
  • Objective assessment
  • Subjective assessment

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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