Most apparent distortion: A dual strategy for full-reference image quality assessment

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7242, Issue , 2009, Pages

  Larson, Eric C ^a   Chandler, Damon M ^a  

^a Oklahoma State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPEARANCE-BASED; FREQUENCY COMPONENTS; HIGH-QUALITY IMAGES; HUMAN VISUAL SYSTEMS; IMAGE QUALITY ASSESSMENTS; LOCAL STATISTICS; LOW QUALITIES; MULTIPLE STRATEGIES; QUALITY ASSESSMENTS; REFERENCE IMAGES; SUBJECT MATTERS; SUBJECTIVE RATINGS;

IMAGE QUALITY;

EID: 62149134875     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.810071     Document Type: Conference Paper

References (49)

1. B. Moulden, F. A. A. Kingdom, and L. F. Gatley, "The standard deviation of luminance as a metric for contrast in random-dot images," Perception 19, pp. 79-101, 1990.
2. J. L. Mannos and D. J. Sakrison, "The effects of a visual fidelity criterion on the encoding of image," IEEE Trans. Info. Theory 20, pp. 525-535, 1974.
3. F. Lukas and Z. Budrikis, "Picture Quality Prediction Based on a Visual Model," IEEE Transactions on Communications 30(7), pp. 1679-1692, 1982.
4. N. Nill, "A Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment," IEEE Transactions on Communications 33(6), pp. 551-557, 1985.
5. S. Daly, "Visible differences predictor: an algorithm for the assessment of image fidelity," in Digital Images and Human Vision, A. B. Watson, ed., pp. 179-206, 1993.
6. P. C. Teo and D. J. Heeger, "Perceptual image distortion," Proc. SPIE 2179, pp. 127-141, 1994.
7. S. J. P. Westen, R. L. Lagendijk, and J. Biemond, "Perceptual image quality based on a multiple channel HVS model," Intl. Conf. Acoustics, Speech, and Signal Processing 4, pp. 2351-2354, 1995.
8. J. Lubin, "A visual discrimination model for imaging system design and evaluation," in Vision Models for Target Detection and Recognition, E. PeIi, ed., pp. 245-283, World Scientific, 1995.
9. C. J. van den Branden Lambrecht, "A working spatio-temporal model of the human visual system for image representation and quality assessment applications," in Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, pp. 2291-2294, May 1996.
10. Y. Lai and C. J. Kuo, "Image quality measurement using the haar wavelet," Proc. SPIE: Wavelet Applications in Signal and Image Processing V, 1997.
11. M. Miyahara, K. Kotani, and V. R. Algazi, "Objective picture quality scale (PQS) for image coding," IEEE Transactions on Communications 46(9), pp. 1215-1226, 1998.
12. W. Osberger, N. Bergmann, and A. Maeder, "An automatic image quality assessment technique incorporating higher level perceptual factors," Proc. IEEE Int. Conf. on Image Processing 3, pp. 414-418, 1998.
13. S. Winkler, "A perceptual distortion metric for digital color images," Proc. IEEE Int. Conf. on Image Processing 3, pp. 399-403, 1998.
14. A. Bradley, "A wavelet visible difference predictor," IEEE Trans. Image Process. 8, pp. 717-730, May 1999.
15. S. Winkler, "Visual quality assessment using a contrast gain control model," in IEEE Signal Processing Society Workshop on Multimedia Signal Processing, pp. 527-532, September 1999.
16. J. Lubin et al., "Method and apparatus for assessing the visibility of differences between two image sequences," 1999. US Patent 5,974,159.
17. "Jndmetrix technology." http://www.sarnoff.com/. Sarnoff Corporation.
18. 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, 2000.
19. M. Carnee, P. L. Callet, and D. Barba, "An image quality assessment method based on perception of structural information," in ICIP 2003, 2, pp. 185-188, 2003.
20. http://foulard.ece.cornell.edu/VSNR.html.
21. Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Trans. Image Process. 13, pp. 600-612, 2004.
22. H. R. Sheikh, A. C. Bovik, and G. de Veciana, "An information fidelity criterion for image quality assessment using natural scene statistics," IEEE Transactions on Image Processing 14(12), pp. 2117-2128, 2005.
23. G. Zhai, W. Zhang, X. Yang, and Y. Xu, "Image quality assessment metrics based on multi-scale edge presentation," IEEE Workshop on Signal Processing Systems Design and Implementation, pp. 331-336, 2005.
24. A. Shnayderman, A. Gusev, and A. M. Eskicioglu, "An SVD-based grayscale image quality measure for local and global assessment," IEEE Trans. Image Processing 15(2), pp. 422-429, 2006.
25. B. Girod, "What's wrong with mean-squared error?," in Digital Images and Human Vision, A. B. Watson, ed., pp. 207-220, 1993.
26. T. N. Pappas, T. A. Michel, and R. O. Hinds, "Supra-threshold perceptual image coding," Proc. ICIP, pp. 237-240, 1996.
27. W. Zeng, S. Daly, and S. Lei, "An overview of the visual optimization tools in jpeg 2000," Signal Processing: Image Communication 17, pp. 85-104, 2001.
28. D. M. Chandler and S. S. Hernami, "Dynamic contrast-based quantization for lossy wavelet image compression," IEEE Trans. Image Process. 14(4), pp. 397-410, 2005.
29. H. R. Sheikh, Z. Wang, A. C. Bovik, , and L. K. Cormack, "Image and video quality assessment research at live." Online, http://live.ece.utexas. edu/research/quality/.
30. R. L. De Valois and K. K. DeValois, Spatial Vision, Oxford University Press, 1990.
31. J. Schulkin, Cognitive Adaptation, Cambridge University Press, 1 ed., 2008.
32. H. R. Sheikh and A. C. Bovik, "Image information and visual quality," IEEE Transactions on Image Processing 15(2), pp. 430-444, 2006.
33. M. Stokes, M. Anderson, S. Chandrasekar, and R. Motta, "A standard default color space for the internetsrgb." http://www.w3.org/Graphics/ Color/sRGB, 1996.
34. S. S. Hernami, D. M. Chandler, B. C. Chern, and J. A. Moses, "Suprathreshold visual psychophysics and structure-based visual masking," in Proc. Visual Communications and Image Processing 2006, J. G. Apostolopoulos and A. Said, eds., 6077, 2006.
35. http://vision.okstate.edu/csiq/.
36. D. M. Chandler and S. S. Hernami, "Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions," J. Opt. Soc. Am. A 20, July 2003.
37. A. K. Jain and F. Farrokhnia, "Unsupervised texture segmentation using gabor filters," Pattern Recognition 24, pp. 1167-1186, May 1991.
38. E. C. Larson and D. M. Chandler, "Explaining crypsis and information content in the visual pathway using statistical properties of animal camouflage and natural scenes," OSA Fall Vision Meeting, 2007.
39. D. J. Field, "Relations between the statistics of natural images and the response properties of cortical cells," J. Opt. Soc. Am. A 4, pp. 2379-2394, 1987.
40. B. A. Olshausen and D. J. Field, "Sparse coding with an overcomplete basis set: A strategy employed by v1?," 37, pp. 3311-3325, Vision Research 1997.
41. F. A. A. Kingdom, A. Hayes, and D. J. Field, "Sensitivity to contrast histogram differences in synthetic wavelet-textures," Vis. Res. 41, pp. 585-598, 1995.
42. P. Kosevi, Invariant Measures of Image Features from Phase Information. PhD thesis, University of Western Australia, 1996.
43. D. M. Chandler and S. S. Hernami, "Suprathreshold image compression based on contrast allocation and global precedence," in Proc. SPIE Human Vision and Electronic Imaging VIII, B. E. Rogowitz and T. N. Pappas, eds., Proceeding SPIE Human Vision and Electronic Imaging, (Santa Clara, CA), 2003.
44. D. M. Chandler and S. S. Hemai, "Vsnr: A wavelet-based visual signal-to-noise ratio for natural images," IEEE Trans. Image Processing 16(9), pp. 2284-2298, 2007.
45. Z. W. H. R. Sheikh, A. C. Bovik, and L. K. Cormack. Image and Video Quality Assessment Research at LIVE [Online], Available: http://live.ece.utexas. edu/research/quality/.
46. "Mad online supplement." http://lena.ceat.okstate.edu/ MADsupplement. Oklahoma State University Image Coding and Analysis lab.
47. VQEG, "Final report from the video quality experts group on the validation of objective models of video quality assessment, phase ii," August 2003. http://www.vqeg.org.
48. H. Sheikh, M. Sabir, and A. Bovik, "A statistical evaluation of recent full reference image quality assessment algorithms," 15, pp. 1349-1364, IEEE Transactions on Image Processing 2006.
49. A. K. Bera and C. M. Jarque, "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Econ. Letters 6, pp. 255-259, 1980.