Reduced reference image quality assessment using regularity of phase congruency

Signal Processing: Image Communication

Volumn 29, Issue 8, 2014, Pages 844-855

  Liu, Delei ^a   Xu, Yong ^a   Quan, Yuhui ^a   Callet, Patrick Le ^b  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSITÉ DE NANTES   (France)

Author keywords

Fractal dimension; Phase congruency; Reduced reference image quality assessment

Indexed keywords

FRACTAL DIMENSION;

BENCHMARK DATABASE; DISTORTED IMAGES; IMAGE FEATURES; IMAGE STRUCTURES; PHASE CONGRUENCY; REDUCED-REFERENCE IMAGE QUALITY ASSESSMENTS; REFERENCE IMAGE;

IMAGE QUALITY;

EID: 84923365354     PISSN: 09235965     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.image.2014.06.007     Document Type: Article

References (51)

1. Z. Wang, and A. Bovik Modern Image Quality Assessment 2006 Morgan & Claypool Publishers
2. A. Rehman, and Z. Wang Reduced-reference image quality assessment by structural similarity estimation IEEE Trans. Image Process. 21 8 2012 3378 3389
3. Z. Wang, G. Wu, H.R. Sheikh, E.P. Simoncelli, E.H. Yang, and A.C. Bovik Quality-aware images IEEE Trans. Image Process. 15 6 2006 1680 1689
4. H.R. Sheikh, and A.C. Bovik Image information and visual quality IEEE Trans. Image Process. 15 2 2006 430 444
5. N. Damera-Venkata, T.D. Kite, W.S. Geisler, B.L. Evans, and A.C. Bovik Image quality assessment based on a degradation model IEEE Trans. Image Process. 9 4 2000 636 650
6. L. Zhang, L. Zhang, X.Q. Mou, and D. Zhang FSIM a feature similarity index for image quality assessment IEEE Trans. Image Process. 20 8 2011 2378 2386
7. H.R. Sheikh, A.C. Bovik, and L.K. Cormack No-reference quality assessment using natural scene statistics JPEG2000 IEEE Trans. Image Process. 14 11 2005 1918 1927
8. Z. Wang, A.C. Bovik, B.L. Evans, Blind measurement of blocking artifacts in images, in: Proceedings of IEEE International Conference Image Processing, vol. 3, 2000, pp. 981-984.
9. Z. Wang, H.R. Sheikh, A.C. Bovik, No-reference perceptual quality assessment of JPEG compressed images, in: Proceedings of IEEE International Conference Image Processing, vol. 1, 2002, pp. 477-480.
10. X. Gao, W. Lu, D. Tao, and X. Li Image quality assessment based on multiscale geometric analysis IEEE Trans. Image Process. 18 7 2009 1409 1423
11. U. Engelke, M. Kusuma, H.J. Zepernick, and M. Caldera Reduced-reference metric design for objective perceptual quality assessment in wireless imaging Signal Process. Image Commun. 24 7 2009 525 547
12. Q. Li, Z. Wang, Reduced-reference image quality assessment using divisive normalization-based image representation, IEEE J. Sel. Top. Signal Process. 3 (2) (2009) 202-211 (special issue on Visual Media Quality Assessment).
13. R. Soundararajan, and A.C. Bovik RRED indices Reduced reference entropic differencing for image quality assessment IEEE Trans. Image Process. 21 2 2012 517 526
14. Z. Wang, E.P. Simoncelli, Reduced-reference image quality assessment using a wavelet-domain natural image statistic model, in: Human Vision and Electronic Imaging X, Proc. SPIE, san Jose, CA, vol. 5666, 2005, pp. 149-159.
15. W.F. Xue, X.Q. Mou, Reduced reference image quality assessment based on Weibull statistics, in: Proceedings of the International Workshop on Quality of Multimedia Experience, 2010, pp. 1-6.
16. L. Ma, S.N. Li, F. Zhang, K.N. Ngan, Reduced-reference image quality assessment using reorganized DCT-based image representation, IEEE Trans. Multim. 13 (3).
17. A.A. Abdelouahad, M.E. Hassouni, H. Cherifi, D. Aboutajdine, Image quality assessment based on IMF coefficients modeling, in: Proceedings of the International Conference on Digital Information and Communication Technology and its Applications, 2011, pp. 131-145.
18. I.P. Gunawanand, M. Ghanbari, Reduced reference picture quality estimation by using local Harmonic amplitude information, in: Proceedings of London Communications Symposium, 2003, pp. 137-140.
19. M. Morrone, J. Ross, D. Burr, and R. Owens Mach bands are phase dependent Nature 324 6094 1986 250 253
20. M. Morrone, and R. Owens Feature detection from local energy Pattern Recognit. Lett. 6 5 1987 303 313
21. M. Morrone, and D. Burr Feature detection in human vision a phase-dependent energy model Proc. R. Soc. Lond. B Biol. Sci. 1988 221 245
22. P. Kovesi Image features from phase congruency Videre: J. Comput. Vis. Res. 1 3 1999 1 26
23. L. Henriksson, A. Hyvärinen, and S. Vanni Representation of cross-frequency spatial phase relationships in human visual cortex J. Neurosci. 29 45 2009 14342 14351
24. A. Saha, and Q. Jonathan Wu Perceptual image quality assessment using phase deviation sensitive energy features Signal Process. 93 11 2013 3182 3191
25. Z. Liu, and R. Laganière Phase congruence measurement for image similarity assessment Pattern Recognit. Lett. 28 1 2007 166 172
26. C. Li, A. Bovik, and X. Wu Blind image quality assessment using a general regression neural network IEEE Trans. Neural Netw. 22 5 2011 793 799
27. R. Hassen, Z. Wang, M. Salama, No-reference image sharpness assessment based on local phase coherence measurement, in: 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, pp. 2434-2437.
28. T.M. Kusuma, H.J. Zepernick, A reduced-reference perceptual quality metric for inservice image quality assessment, in: Proceedings of Workshop on Mobile Future and Symposium on Trends in Communications, 2003, pp. 71-74.
29. Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli Image quality assessment from error visibility to structural similarity IEEE Trans. Image Process. 13 4 2004 600 612
30. Y. Xu, H. Ji, and C. Fermüller Viewpoint invariant texture description using fractal analysis Int. J. Comput. Vis. 83 1 2009 85 100
31. A. Oppenheim, and J. Lim The importance of phase in signals Proc. IEEE 69 5 1981 529 541
32. P. Kovesi, A dimensionless measure of edge significance from phase congruency calculated via wavelets, in: First New Zealand Conference on Image and Vision Computing, 1993, pp. 87-94.
33. B.B. Mandelbrot The Fractal Geometry of Nature 1982 Freeman San Francisco, CA
34. N. Sarkar, and B.B. Chaudhuri An efficient differential box-counting approach to compute fractal dimension of image IEEE Trans. Syst. Man Cybernet. 24 1 1994 115 120
35. S.S. Chen, Fractal geometry in image understanding (Ph.D. dissertation), University of Missouri-Columbia, 1987.
36. A.S. Balghonaim, and J.M. Keller A maximum likelihood estimate for two-variable fractal surface IEEE Trans. Image Process. 7 12 1997 1746 1753
37. A.P. Pentland Fractal-based description of natural scenes IEEE Trans. Pattern Anal. Mach. Intell. 6 6 1984 661 674
38. A. Liu, W. Lin, and M. Narwaria Image quality assessment based on gradient similarity IEEE Trans. Image Process. 21 4 2012 1500 1512
39. G.-H. Chen, C.-L. Yang, S.-L. Xie, Gradient-based structural similarity for image quality assessment, in: 2006 IEEE International Conference on Image Processing, 2006, pp. 2929-2932.
40. D.-O. Kim, H.-S. Han, and R.-H. Park Gradient information-based image quality metric IEEE Trans. Consum. Electron. 56 2 2010 930 936
41. H.R. Sheikh, K. Seshadrinathan, A.K. Moorthy, Z. Wang, A.C. Bovik, L.K. Cormack, Image and video quality assessment research at LIVE, http://live.ece.utexas.edu/research/quality.
42. N. Ponomarenko, V. Lukin, A. Zelensky, K. Egiazarian, M. Carli, and F. Battisti TID2008 - a database for evaluation of full-reference visual quality assessment metrics Adv. Modern Radioelectron. 10 10 2009 30 45
43. E.C. Larson, D.M. Chandler, Categorical Image Quality (CSIQ) Database, http://vision.okstate.edu/csiq .
44. A. Ninassi, P.L. Callet, F. Autrusseau, Subjective quality assessment-IVC database, http://www2.irccyn.ec-nantes.fr/ivcdb .
45. Y. Horita, K. Shibata, Y. Kawayoke, Z.M.P. Sazzad, MICT image quality evaluation database, http://mict.eng.u-toyama.ac.jp/mict/index2.html .
46. U. Engelke, H.J. Zepernick, M. Kusuma, Wireless imaging quality database, http://www.bth.se/tek/rcg.nsf/pages/wiq-db (2010).
47. D.M. Chandler, S.S. Hemami, A57 database, http://foulard.ece.cornell.edu/ dmc27/vsnr/vsnr.html .
48. VQEG, Final report from the video quality experts group on the validation of objective models of video quality assessment, http://www.vqeg.org , 2000.
49. H.R. Sheikh, M.F. Sabir, and A.C. Bovik A statistical evaluation of recent full reference image quality assessment algorithms IEEE Trans. Image Process. 15 11 2006 3440 3451
50. Z. Wang, and Q. Li Information content weighting for perceptual image quality assessment IEEE Trans. Image Process. 20 5 2011 1185 1198
51. Z. Wang, SSIM Index for image quality assessment, https://ece.uwaterloo. ca/%7Ez70wang/research/ssim/ .