Modeling subjectively perceived annoyance of H.264/AVC video as a function of perceived artifact strength

Signal Processing

Volumn 90, Issue 1, 2010, Pages 80-92

  Wolff, Tobias ^a   Ho, Hsin Han ^b   Foley, John M ^c   Mitra, Sanjit K ^b  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^b University of California   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Coding artifacts; Data analysis; H.264 AVC; Modeling; Subjectively perceived annoyance; Video quality

Indexed keywords

CODING ARTIFACTS; DATA ANALYSIS; H.264/AVC; MODELING; SUBJECTIVELY PERCEIVED ANNOYANCE; VIDEO QUALITY;

COLOR PHOTOGRAPHY; EXPERIMENTS; IMAGE CODING; VIDEO RECORDING; VISUAL COMMUNICATION;

MOTION PICTURE EXPERTS GROUP STANDARDS;

EID: 69249206555     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.05.018     Document Type: Article

References (21)

1. M.C.Q. Farias, No-reference and reduced reference video quality metrics: new contributions, Ph.D. Dissertation, Department of Electrical and Computer Engineering, University of California Santa Barbara, September 2004.
2. Wiegand T., Sullivan G.J., Bjøntegaard G., and Luthra A. Overview of the H.264/AVC video coding standard. IEEE Transactions on Circuits and Systems for Video Technology 13 7 (2003) 560-576
3. D. Marpe, T. Wiegand, H.264/MPEG4-AVC fidelity range extensions: tools, profiles, performance and application areas, Fraunhofer Institute for Telecommunications-Heinrich Hertz Institute (HHI), Image Processing Department, Berlin, Germany.
4. Papoulis A. Probability, Random Variables and Stochastic Processes. third ed. (1991), McGraw-Hill Book Company, New York
5. C.C. Koh, S.K. Mitra, J.M. Foley, I.E.J. Heynderickx, Annoyance of individual artifacts in MPEG-2 compressed video and their relation to overall annoyance, in: Proceedings of the IS&T/SPIE Symposium on Electronic Imaging: Human Vision and Electronic Imaging X, vol. 5666, January 2005, pp. 595-606.
6. H. De Ridder, Minkowski-metrics as a combination rule for digital-image-coding impairments, in: Proceedings of the SPIE Human Vision, Visual Processing, and Digital Display III, vol. 1666, April 1992, pp. 16-26.
7. M. Yuen, H.R. Wu, A survey of hybrid MC/DPCM/DCT video coding distortions, Signal Processing 70 (3).
8. List P., Joch A., Lainema J., Bjøntegaard G., and Karczewicz M. Adaptive deblocking filter. IEEE Transactions on Circuits and Systems for Video Technology 13 7 (July 2003) 614-619
9. Y. Zhong, I. Richardson, A. Miller, Y. Zhao, Perceptual quality of H.264/AVC de-blocking filter, in: Proceedings of the IEEE International Conference on Visual Information Engineering (VIE 2005), Glasgow, April 2005, pp. 379-384.
10. Chun S.S., Kim J.R., and Sull S. Intra prediction mode selection for Flicker reduction in H.264/AVC. IEEE Transactions on Consumer Electronics 52 4 (November 2006) 1303-1310
11. T. Wolff, H.264 coding artifacts and their relation to perceived annoyance-a granularity based approach, Diploma Thesis, Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, Germany, December 2005.
12. T. Wolff, H. Ho, J.M. Foley, S.K. Mitra, H.264 coding artifacts and their relation to perceived annoyance, in: Proceedings of the European Signal Processing Conference (EUSIPCO 06), Florence, Italy, September 2006.
13. Hoel P.G. Introduction to Mathematical Statistics (1984), Wiley, New York
14. G. Stumme, K.E. Wolff, Numerical aspects in the data model of conceptual information systems, in: Proceedings of the Workshops on Data Warehousing and Data Mining. Advances in Database Technologies, Lecture Notes in Computer Science, vol. 1552, Springer, London, UK, 1999, pp. 117-128.
15. Wille R. Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I. (Ed). Ordered Sets (1989), Reidel, Dordrecht, Boston 445-470
16. Ganther B., and Wille R. Formal Concept Analysis-Mathematical Foundations (1999), Springer, Berlin, Heidelberg, New York
17. K.E. Wolff, T. Wolff, Comparing conceptual and statistical approaches: a case study in image processing. Conceptual structures: inspiration and application, in: P. Hitzler, H. Schärfe, P. Øhrstrøm (Eds.), Contributions to ICCS 06. 14th International Conference on Conceptual Structures, Aarlborg, 2006, pp. 230-245.
18. Nelder J.A., and Mead R. A simplex method for function minimization. Computer Journal 7 (1965) 308-313
19. International Telecommunication Union, Geneva, Switzerland, ITU-T Recommendation B.500-8: methodology for the subjective assessment of the quality of television pictures, 1998.
20. Moore M., Foley J.M., and Mitra S.K. Defect visibility and content importance: effects on perceived impairments. Image Communication 3 (February 2004) 185-203
21. Farias M.C.Q., Foley J.M., and Mitra S.K. Detectability and annoyance of synthetic blurry, blocky, noisy, and ringing artifacts. IEEE Transactions on Signal Processing 55 6 (June 2007) 2954-2964