research-article

Content and quality: Interpretation-based estimation of image quality

Authors:

Jukka Häkkinen,

Jean-Luc Olives,

Göte NymanAuthors Info & Claims

ACM Transactions on Applied Perception (TAP), Volume 4, Issue 4

Article No.: 2, Pages 1 - 15

https://doi.org/10.1145/1278760.1278762

Published: 11 February 2008 Publication History

Abstract

Test image contents affect subjective image-quality evaluations. Psychometric methods might show that contents have an influence on image quality, but they do not tell what this influence is like, i.e., how the contents influence image quality. To obtain a holistic description of subjective image quality, we have used an interpretation-based quality (IBQ) estimation approach, which combines qualitative and quantitative methodology. The method enables simultaneous examination of psychometric results and the subjective meanings related to the perceived image-quality changes. In this way, the relationship between subjective feature detection, subjective preferences, and interpretations are revealed. We report a study that shows that different impressions are conveyed in five test image contents after similar sharpness variations. Thirty naïve observers classified and freely described the images after which magnitude estimation was used to verify that they distinguished the changes in the images. The data suggest that in the case of high image quality, the test image selection is crucial. If subjective evaluation is limited only to technical defects in test images, important subjective information of image-quality experience is lost. The approach described here can be used to examine image quality and it will help image scientists to evaluate their test images.

References

[1]

Avadhanam, N. and Algazi V. R. 1998. Electronic imaging, SPIE 3308, 44--53.

[2]

Bakeman, R. and Gottman, J. M. 1986. Observing Interaction: An Introduction to Sequential Analysis. Cambridge University Press, Cambridge.

[3]

Barten, P. 1999. Contrast Sensitivity of the Human Eye and Its Effects on Image Quality. SPIE, Bellingham, WA.

[4]

Bech, S., Hamberg, R., Nijenhuis, M., Teunissen, C., Looren de Jong, H., Houben, P., and Pramanik, S. K. 1996. The RaPID perceptual image description method (RaPID). SPIE 2657, 317--328.

[5]

Boreman, G. 2001. Modulation Transfer Function in Optical and Electro-Optical Systems. SPIE, Bellingham, WA. VOL TT52.

[6]

Cicchetti, D. 1994. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment 6, 284--290.

[7]

Cui, C. 2004. Do experts and naïve observers judge printing quality differently&quest; Electronic Imaging, SPIE 5294, 132--145.

[8]

Eckert, M. P. and Bradley, A. P. 1998. Perceptual quality metrics applied to still image compression. Signal Processing 70, 177--200.

Digital Library

[9]

Engeldrum, P. G. 2000. Psychometric Scaling: A Toolkit for Imaging System Development. Imcotek Press, Winchester, MA.

[10]

Faye, P., Brémaud, D., Daubin, M. D.,Courcoux, P., Giboreau, A., and Nicod, H. 2004. Perceptive free sorting and verbalization tasks with naïve subjects: An alternative to descriptive mappings. Food Quality and Preference 15, 781--791.

[11]

Fedorovskaya, E. A., De Ridder, H., and Blommaert, F. J. J. 1997. Chroma variations and perceived quality of color images of natural scenes. COLOR Research and Application 22, 96--110.

[12]

Hair, J., Anderson, R., Tatham, R., and Black, W. 1998. Multivariate Data Analysis. Prentice Hall, Englewood Cliffs, New Jersey, USA.

Digital Library

[13]

Heynderickx, I. and Bech, S. 2002. Image quality assessment by expert and non-expert viewers. In Proceedings of SPIE 4662, 129--137.

[14]

ISO Standard 12640. 1997. Standard Colour Images Digital Data, International Standards Organization.

[15]

Keelan, B. W. 2002. Handbook of Image Quality---Characterization and Prediction, Marcel Decker, New York.

[16]

Keelan, B. W. and Urabe, H. 2004. ISO 20462, A psychological image quality measurement standard, In Image Quality and System Performance, 2004. Y. Miyake and R. Rasmussen, Eds. Proceedings of SPIE- IS&T Electronic Imaging 5294. 181--189.

[17]

Nijenhuis, M. Hamberg, R., Teunissen, C., Bech, S., Looren de Jong, H., Houben, P., and Pramanik, S. K. 1997. Sharpness, sharpness related attributes, and their physical correlates, SPIE 3025. 173--194.

[18]

Nyman, G. 2002. Quality Experience Research: Trying to Understand the Modern Magazine Reader in Multimedia World. Presentation at PPA, London, UK. 2002.

[19]

Nyman, G., Radun, J., Leisti, T. and Vuori, T. 2005. From image fidelity to subjective quality: A hybrid qualitative/quantitative methodology for measuring subjective image quality for different image contents. In Proc. 12 th International Display Workshops (IDW '05), Takamatsu, Japan, (Dec.). 1825--1828.

[20]

Nyman, G., Radun, J., Leisti, T., Oja, J., Ojanen, H., Olives, J. L., Vuori, T., and Häkkinen, J. 2006. What do users really perceive: Probing the subjective image quality. In Image Quality and System Performance III. L. C. Cui and Y. Miyake, Eds. Proceedings of SPIE-IS&T Electronic Imaging 6059, 1--7.

[21]

Picard, D., Dacremont, C., Valentin, D., and Giboreau, A. 2003. Perceptual dimensions of tactile textures. Acta Psychologica 114, 165--184.

[22]

Silverstein, D. A. and Farrell, J. E. 1996. The relationship between image fidelity and image quality. IEEE, 881--884.

[23]

Strauss, A. and Corbin, J. 1998. Basics of qualitative research. 2nd ed., Sage, Thousand Oaks, CA.

[24]

Vqeg. 2000. Final report from the video quality experts group on the validation of objective models of video quality assessment. http://www.its.bldrdoc.gov/vqeg/projects/frtv_phaseI/COM-80E_final_report.pdf

[25]

Wang, Z., Bovik, A. C., and Lu, L. 2002. Why is image quality assessment so difficult&quest; IEEE International Conference on Acoustics, Speech, & Signal Processing, (May). 2002.

[26]

Yendrikhovskij, S., MacDonald, L., Bech, S., and Jensen, K. 1999. Enhancing colour image quality in television displays. The Imaging Science Journal 47, 197--211.

Cited By

Kazienko PBielaniewicz JGruza MKanclerz KKaranowski KMiłkowski PKocoń J(2023)Human-centered neural reasoning for subjective content processing: Hate speech, emotions, and humorInformation Fusion10.1016/j.inffus.2023.01.01094(43-65)Online publication date: Jun-2023
https://doi.org/10.1016/j.inffus.2023.01.010
Park DJeong YMoon YPark Y(2023)Observation of image quality for HDR micro LED displayDisplays10.1016/j.displa.2023.10249879(102498)Online publication date: Sep-2023
https://doi.org/10.1016/j.displa.2023.102498
Kadyrova APedersen MWestland S(2022)Effect of Elevation and Surface Roughness on Naturalness Perception of 2.5D Decor PrintsMaterials10.3390/ma1509337215:9(3372)Online publication date: 8-May-2022
https://doi.org/10.3390/ma15093372
Show More Cited By

Index Terms

Content and quality: Interpretation-based estimation of image quality
1. Applied computing
  1. Law, social and behavioral sciences
    1. Psychology
  2. Operations research
    1. Consumer products

Recommendations

Evaluating the multivariate visual quality performance of image-processing components

The estimation of image quality is a demanding task, especially when estimating different high-quality imaging products or their components. The challenge is the multivariate nature of image quality as well as the need to use naïve observers as test ...
A new method for evaluating the subjective image quality of photographs: dynamic reference

The Dynamic Reference (DR) method has been developed for subjective image quality experiments in which original or undistorted images are unavailable. The DR method creates reference image series from test images. Reference images are presented to ...
Objective quality assessment of color images based on a generic perceptual reduced reference

When an image is supposed to have been transformed by a process like image enhancement or lossy image compression for storing or transmission, it is often necessary to measure the quality of the distorted image. This can be achieved using an image ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Applied Perception

ACM Transactions on Applied Perception Volume 4, Issue 4

January 2008

112 pages

ISSN:1544-3558

EISSN:1544-3965

DOI:10.1145/1278760

Issue’s Table of Contents

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 February 2008

Accepted: 01 September 2006

Revised: 01 August 2006

Received: 01 May 2006

Published in TAP Volume 4, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Pre-selected

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

32
Total Citations
View Citations
875
Total Downloads

Downloads (Last 12 months)21
Downloads (Last 6 weeks)10

Reflects downloads up to 19 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kazienko PBielaniewicz JGruza MKanclerz KKaranowski KMiłkowski PKocoń J(2023)Human-centered neural reasoning for subjective content processing: Hate speech, emotions, and humorInformation Fusion10.1016/j.inffus.2023.01.01094(43-65)Online publication date: Jun-2023
https://doi.org/10.1016/j.inffus.2023.01.010
Park DJeong YMoon YPark Y(2023)Observation of image quality for HDR micro LED displayDisplays10.1016/j.displa.2023.10249879(102498)Online publication date: Sep-2023
https://doi.org/10.1016/j.displa.2023.102498
Kadyrova APedersen MWestland S(2022)Effect of Elevation and Surface Roughness on Naturalness Perception of 2.5D Decor PrintsMaterials10.3390/ma1509337215:9(3372)Online publication date: 8-May-2022
https://doi.org/10.3390/ma15093372
Leisti TVaahteranoksa MOlives JPeltoketo VHäkkinen J(2022)The Fewer Reasons, the More You Like It! How Decision-Making Heuristics of Image Quality Estimation Exploit the Content of Subjective ExperienceFrontiers in Psychology10.3389/fpsyg.2022.86787413Online publication date: 21-Jun-2022
https://doi.org/10.3389/fpsyg.2022.867874
Uhrig SUhrig S(2021)General DiscussionHuman Information Processing in Speech Quality Assessment10.1007/978-3-030-71389-8_8(149-158)Online publication date: 12-Mar-2021
https://doi.org/10.1007/978-3-030-71389-8_8
Wedel SKoppetz MSkowronek JRaake AAmsaleg LHuet BLarson MGravier GHung HNgo CTsang Ooi W(2019)ViProVoQProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3351171(2387-2395)Online publication date: 15-Oct-2019
https://dl.acm.org/doi/10.1145/3343031.3351171
Park DPark Y(2018)The characteristic of image quality perception of elderly group: according to the comparison with adult groupJournal of Information Display10.1080/15980316.2018.147627219:3(111-120)Online publication date: 29-May-2018
https://doi.org/10.1080/15980316.2018.1476272
Radun JNuutinen MLeisti THäkkinen J(2016)Individual Differences in Image-Quality EstimationsACM Transactions on Applied Perception10.1145/289050413:3(1-22)Online publication date: 28-May-2016
https://dl.acm.org/doi/10.1145/2890504
Teich SAl-Rawi WHeima MFaddoul FGoldzweig GGutmacher ZAizenbud D(2016)Image quality evaluation of eight complementary metal-oxide semiconductor intraoral digital X-ray sensorsInternational Dental Journal10.1111/idj.1224166:5(264-271)Online publication date: 22-Apr-2016
https://doi.org/10.1111/idj.12241
Streijl RWinkler SHands D(2016)Mean opinion score (MOS) revisitedMultimedia Systems10.1007/s00530-014-0446-122:2(213-227)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1007/s00530-014-0446-1
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents