Comparison of image quality assessment algorithms on compressed images

Christophe Charrier, Kenneth Knoblauch, Anush K. Moorthy, Alan C. Bovik, Laurence T. Maloney

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


A crucial step in image compression is the evaluation of its performance, and more precisely the available way to measure the final quality of the compressed image. Usually, to measure performance, some measure of the covariation between the subjective ratings and the degree of compression is performed between rated image quality and algorithm. Nevertheless, local variations are not well taken into account. We use the recently introduced Maximum Likelihood Difference Scaling (MLDS) method to quantify suprathreshold perceptual differences between pairs of images and examine how perceived image quality estimated through MLDS changes the compression rate is increased. This approach circumvents the limitations inherent to subjective rating methods.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Image Quality and System Performance VII
StatePublished - 2010
EventImage Quality and System Performance VII - San Jose, CA, United States
Duration: Jan 18 2010Jan 19 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherImage Quality and System Performance VII
Country/TerritoryUnited States
CitySan Jose, CA


  • Maximum-likelihood difference scaling
  • Quality assessment

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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