Image dissimilarity

Signal Processing

Volumn 70, Issue 3, 1998, Pages 155-176

  Martens, Jean Bernard ^a   Meesters, Lydia ^a  

^a Institute for Perception Research Eindhoven   (Netherlands)

Author keywords

Image dissimilarity; Image quality metric; Instrumental measures; Objective image quality; Subjective image quality; Vision models

Indexed keywords

IMAGE QUALITY; SPURIOUS SIGNAL NOISE;

IMAGE DISSIMILARITY;

IMAGE PROCESSING;

EID: 0032202184     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1684(98)00123-6     Document Type: Article

References (32)

1. A.J. Ahumada Jr., Computational image-quality metrics: a review, in: SID 93 Digest, Society for Information Display, Santa Ana, CA, 1993. pp. 305-308.
2. P.G.J. Barten, The sqri method: a new method for the evaluation of visible resolution on a display, Proc. Soc. Inform. Disp. 30 (1987) 253-262.
3. M.C. Boschman, J.A.J. Roufs, Text quality metrics for visual display units: ii. an experimental survey, Displays 18 (1997) 45-64.
4. P.J. Burt, E. Adelson, The laplacian pyramid as a compact image code, IEEE Trans. Commun. 31 (April 1983) 532-540.
5. M.W. Cannon, S.C. Fullenkamp, A transducer model for contrast perception, Vision Res. 31 (1991) 983-998.
6. S. Daly, Visible differences predictor: an algorithm for the assessment of image fidelity, in: B.E. Rogowitz, (Ed.), Human Vision, Visual Processing, and Digital Display III, Proc. SPIE, Vol. 1666, 1992, pp. 2-15.
7. S. Daly, Visible differences predictor: an algorithm for the assessment of image fidelity, in: A.B. Watson (Ed.), Digital Images and Human Vision, MIT Press, Cambridge, MA, 1993, pp. 179-206.
8. B. Escalante-Ramírez, J.B. Martens, H. de Ridder, Multidimensional characterization of the perceptual quality of noise-reduced computed tomography images, J. Visual Commun. Image Representation 6 (December 1995) 317-334.
9. D.K. Fibush, Practical application of objective picture quality measurements, in: IBC97, International Broadcast Union, 1997, pp. 123-135.
10. W.T. Freeman, E.H. Adelson, The design and use of steerable filters, IEEE Trans. Pattern Anal. Mach. Intell. 13 (September 1991) 891-906.
11. ITU, Method for the subjective assessment of the quality of television pictures, Technical Report ITU Recommendation 500-3, International Television Union, Geneva, 1992.
12. V. Kayargadde, J.B. Martens, Perceptual characterization of images degraded by blur and noise: experiments, J. Opt. Soc. Amer. A 13 (June 1996) 1166-1177.
13. V. Kayargadde, J.B. Martens, Perceptual characterization of images degraded by blur and noise: model, J. Opt. Soc. Amer. A 13 (June 1996) 1178-1188.
14. J.B. Kruskal, M. Wish, Multidimensional Scaling, Sage University Paper Series 07-011 on Quantitative Applications in the Social Sciences, Sage Publications, Beverley Hills, CA, 1978.
15. P. Lindh, C.J. van den Branden Lambrecht, Efficient spatio-temporal decomposition for perceptual processing of video sequences, in: IEEE Internat. Conf. on Image Processing, Vol. III of III, Lausanne, Switzerland, September 1996, pp. 331-334.
16. J. Lubin, The use of psychophysical data and models in the analysis of display system performance, in: A.B. Watson (Ed.), Digital Images and Human Vision, MIT Press, Cambridge, MA, 1993, pp. 162-178.
17. J. Lubin, A visual discrimination model for imaging system design and evaluation, in: E. Peli (Ed.), Visual Models for Target Detection and Recognition, World Scientific, River Edge, NJ, 1995.
18. J.-B. Martens, Adaptive contrast enhancement through residue-image processing, Signal Processing 44 (1995) 1-18.
19. L. Meesters, J.B. Martens, Blockiness estimation in jpeg-coded images, Internal communication.
20. E. Peli, Contrast in complex images, J. Opt. Soc. Amer. A 7 (1990) 2032-2040.
21. W.B. Pennebaker, J.L. Mitchell, JPEG Still Image Compression Standard, Van Nostrand Reinhold, New York, 1993.
22. J.O. Ramsay, Maximum likelihood estimation in multidimensional scaling, Psychometrika 42 (1977) 241-266.
23. J.O. Ramsay, Confidence regions for multidimensional scaling analysis, Psychometrika 43 (1978) 145-160.
24. J.O. Ramsay, J. ten Berge, G.P.H. Styan, Matrix correlation, Psychometrika 49 (September 1984) 403-423.
25. D.A. Silverstein, J.E. Farell, The relationship between image fidelity and image quality, in: IEEE Internat. Conf. on Image Processing, Lausanne, Switzerland, September 1996, pp. 881-884.
26. S.S. Stevens, On the psychophysical law, Psychol. Rev. 64 (1957) 153-181.
27. J.M.F. Ten Berge, Orthogonal procrustes rotation for two or more matrices, Psychometrika 42 (1977) 267-276.
28. P. Teo, D. Heeger, Perceptual image distortion, in: IEEE Internat. Conf. on Image Processing, Austin, TX, November 1994, pp. 982-984.
29. W.S. Torgerson, Theory and Methods of Scaling, Wiley, New York, 1958.
30. C.J. van den Branden Lambrecht, Color moving pictures quality metric, in: IEEE Internat Conf. on Image Processing, Vol. I of III, Lausanne, Switzerland, September 1996, pp. 885-888.
31. C.J. van den Branden Lambrecht, Perceptual models and architectures for video coding applications, Ph.D. Thesis, Ecole Polytechnique Fédérale de Lausanne, Switzerland, 1996.
32. C. Zetzsche, G. Hauske, Multiple channel model for the prediction of subjective image quality, in: B.E. Rogowitz (Ed.), Human Vision, Visual Processing, and Digital Display, Proc. SPIE, Vol. 1077, 1989, pp. 209-216.