Literature DB >> 7500220

Continuous assessment of perceptual image quality.

R Hamberg1, H de Ridder.   

Abstract

The study addresses whether subjects are able to assess the perceived quality of an image sequence continuously. To this end, a new method for assessing time-varying perceptual image quality is presented by which subjects continuously indicate the perceived strength of image quality by moving a slider along a graphical scale. The slider's position on this scale is sampled every second. In this way, temporal variations in quality can be monitored quantitatively, and a means is provided by which differences between, for example, alternative transmission systems can be analyzed in an informative way. The usability of this method is illustrated by an experiment in which, for a period of 815 s, subjects assessed the quality of still pictures comprising time-varying degrees of sharpness.

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Year:  1995        PMID: 7500220     DOI: 10.1364/josaa.12.002573

Source DB:  PubMed          Journal:  J Opt Soc Am A Opt Image Sci Vis        ISSN: 1084-7529            Impact factor:   2.129


  5 in total

1.  Recognition performance and perceived quality of video enhanced for the visually impaired.

Authors:  Eli Peli
Journal:  Ophthalmic Physiol Opt       Date:  2005-11       Impact factor: 3.117

2.  IMAGE ENHANCEMENT FOR IMPAIRED VISION: THE CHALLENGE OF EVALUATION.

Authors:  Eli Peli; Russell L Woods
Journal:  Int J Artif Intell Tools       Date:  2009-06       Impact factor: 1.208

3.  Measuring perceived video quality of MPEG enhancement by people with impaired vision.

Authors:  Matthew Fullerton; Russell L Woods; Fuensanta A Vera-Diaz; Eli Peli
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2007-12       Impact factor: 2.129

4.  A psychophysical performance-based approach to the quality assessment of image processing algorithms.

Authors:  Daniel H Baker; Robert J Summers; Alex S Baldwin; Tim S Meese
Journal:  PLoS One       Date:  2022-05-05       Impact factor: 3.240

5.  Measuring information acquisition from sensory input using automated scoring of natural-language descriptions.

Authors:  Daniel R Saunders; Peter J Bex; Dylan J Rose; Russell L Woods
Journal:  PLoS One       Date:  2014-04-02       Impact factor: 3.240

  5 in total

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