Abstract
In this paper we investigate if the Difference of Gaussians model is able to predict observers perceived difference in relation to compression artifacts. A new image difference metric for specifically designed for compression artifacts is proposed. In order to evaluate this new metric a psychophysical experiment is carried out, where a dataset of 80 compressed JPEG and JPEG2000 images were generated from 10 different scenes. The results of the psychophysical experiment with 18 observers and the quality scores obtained from a large number of image difference metrics are presented.
Furthermore, a quantitative study based on a number of image difference metrics and five additional databases is performed in order to reveal the potential of the proposed metric. The analyses show that the proposed metric and most of the tested ones do not correlate well with the subjective test results, and thus the increased complexity of the recent metrics is not justified.
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References
Pedersen, M., Hardeberg, J.Y.: Survey of full-reference image quality metrics. Høgskolen i Gjøviks rapportserie, vol. 5. Gjøvik University College, The Norwegian Color Research Laboratory, Gjøvik, Norway (2009)
Luo, M., Cui, G., Rigg, B.: The development of the CIE 2000 colour-difference formula: CIEDE2000. Color Research and Application 26, 340–350 (2001)
Zhang, X.M., Farrell, J., Wandell, B.: Application of a spatial extension to cielab. In: IS&T/SPIE Electronic Imaging 1997, vol. 3025, pp. 154–157 (1997)
Johnson, G.M.: Measuring images: differences, quality and apperance. PhD thesis, Rochester Institute of Technology (2003)
Johnson, G.M., Fairchild, M.D.: Darwinism of color image difference models. In: IS&T/SID 9th Color Imaging Conference, Scottsdale, AZ, USA, pp. 108–112 (2001)
Hong, G., Luo, M.R.: New algorithm for calculating perceived colour difference of images. Imaging Science Journal 54, 86–91 (2006)
Oleari, C., Melgosa, M., Huertas, R.: Euclidean color-difference formula for small-medium color differences in log-compressed osa-ucs space. Journal of the Optical Society of America 26, 121–134 (2009)
Huertas, R., Melgosa, M., Oleari, C.: Performance of a color-difference formula based on OSA-UCS space using small-medium color differences. Journal of the Optical Society of America 23, 2077–2084 (2006)
Simone, G., Oleari, C., Farup, I.: Performance of the euclidean color-difference formula in log-compressed OSA-UCS space applied to modified image-difference metrics. In: 11th Congress of the International Colour Association (AIC), Sydney, Australia, p. 81 (2009)
Ajagamelle, S.: Analysis of the difference of gaussians model in perceptual image difference metrics. Master’s thesis, Gjøvik University College and Grenoble Institute of Technology (2009)
Ajagamelle, S.A., Pedersen, M., Simone, G.: Analysis of the difference of gaussians model in image difference metrics. In: 5th European Conference on Colour in Graphics, Imaging, and Vision (CGIV), Joensuu, Finland, pp. 489–496 (2010)
Wang, Z., Bovik, A.: A universal image quality index. IEEE Signal Processing Letters 9, 81–84 (2002)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE TIP 13, 600–612 (2004)
Pedersen, M., Bonnier, N., Hardeberg, J.Y., Albregtsen, F.: Attributes of image quality for color prints. Journal of Electronic Imaging 19, 011016-1– 011016-13 (2010)
Tadmor, Y., Tolhurst, D.: Calculating the contrasts that retinal ganglion cells and LGN neurones encounter in natural scenes. Vision Research 40, 3145–3157 (2000)
Simone, G., Pedersen, M., Hardeberg, J.Y.: Measuring perceptual contrast in digital images. Journal of Visual Communication and Image Representation (2010) (under review)
Field, G.G.: Test image design guidelines for color quality evaluation. In: IS&T/SID 7th Color Imaging Conference, Scottsdale, AZ, USA, pp. 194–196 (1999)
CIE: Guidelines for the evaluation of gamut mapping algorithms. Technical Report, CIE TC8-08 (156:2004) ISBN: 3-901-906-26-6
Ponomarenko, N., Lukin, V., Egiazarian, K., Astola, J., Carli, M., Battisti, F.: Color image database for evaluation of image quality metrics, pp. 403–408 (2008), http://www.ponomarenko.info/tid2008.htm
ISO: Graphic techonology - prepress digital echange. Technical report, ISO 12640-2, 1 edn. (2004)
Reinhard, E., Ward, G., Pattanaik, S., Debevec, P.: High Dynamic Range Imaging - Acquisition, Display and Image-Based Lighting. Morgan Kaufmann Publisher, San Francisco (2005)
Le Callet, P.A.: Subjective quality assessment irccyn/ivc database 2005. In: IRCCyN (2005)
Engeldrum, P.G.: Psychometric Scaling. Imcotek Press, Winchester (2000)
Djik, J.: In search of an objective measure for the perceptual quality of printed images. PhD thesis, Technische Unisersitet Delft (2004)
Caracciolo, V.: Just noticeable distortion evaluation in color images. Master’s thesis, Gjøvik University College and Roma Tre University (2009)
Eskicioglu, A., Fisher, P., Chen, S.: Image quality measures and their performance. IEEE Transactions on Communications 43, 2959–2965 (1995)
Pedersen, M.: Importance of region-of-interest on image difference metrics. Master thesis, Gjøvik University College (2007)
Dugay, F., Farup, I., Hardeberg, J.Y.: Perceptual evaluation of color gamut mapping algorithms. Color Research & Application 33, 470–476 (2008)
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Simone, G., Caracciolo, V., Pedersen, M., Cheikh, F.A. (2010). Evaluation of a Difference of Gaussians Based Image Difference Metric in Relation to Perceived Compression Artifacts. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_48
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DOI: https://doi.org/10.1007/978-3-642-17274-8_48
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