Image Quality Assessment in the Modern Age

Kede Ma, Yuming Fang

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

22 Citations (Scopus)

Abstract

This tutorial provides the audience with the basic theories, methodologies, and current progresses of image quality assessment (IQA). From an actionable perspective, we will first revisit several subjective quality assessment methodologies, with emphasis on how to properly select visual stimuli. We will then present in detail the design principles of objective quality assessment models, supplemented by an in-depth analysis of their advantages and disadvantages. Both hand-engineered and (deep) learning-based methods will be covered. Moreover, the limitations with the conventional model comparison methodology for objective quality models will be pointed out, and novel comparison methodologies such as those based on the theory of "analysis by synthesis"will be introduced. We will last discuss the real-world multimedia applications of IQA, and give a list of open challenging problems, in the hope of encouraging more and more talented researchers and engineers devoting to this exciting and rewarding research field.
Original languageEnglish
Title of host publicationMM' 21
Subtitle of host publicationProceedings of the 29th ACM International Conference on Multimedia
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages5664-5666
ISBN (Print)978-1-4503-8651-7
DOIs
Publication statusPublished - 2021
Event29th ACM International Conference on Multimedia (MM 2021) - Hybrid, Chengdu, China
Duration: 20 Oct 202124 Oct 2021
https://2021.acmmm.org/

Publication series

NameMM - Proceedings of the ACM International Conference on Multimedia

Conference

Conference29th ACM International Conference on Multimedia (MM 2021)
Abbreviated titleMM '21
PlaceChina
CityChengdu
Period20/10/2124/10/21
Internet address

Research Keywords

  • image quality assessment
  • model comparison
  • perceptual optimization

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