Abstract
Fractal image coding is a relatively recent technique based on the representation of an image by a map of self-similarities. In last years, most researchers focused their attention on the problem of speeding up the fractal coding process, while paying little attention to possible improvements of the objective and subjective image quality. In this paper, we investigate image quality measures, which could represent a reasonable alternative to the RMSE when finding a suitable map of similarities. Subjective assessments have been performed in order to compare performances of the selected quality metrics. Experimental results bear witness to the superiority of such a quality metric based on Fourier coefficients.
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References
Acivbas, I., Sankur, B., Sayood, K.: Statistical evaluation of image quality measures. Fournal of Electronic Imaging 11(2), 206–223 (2002)
Ahmed, N., Natarajan, T., Rao, K.R.: Discrete Cosine Transform. In: IEEE Transaction on Computers, pp. 90–93. IEEE Computer Society Press, Los Alamitos (1974)
De Oliveira, J.F.L., Mendoça, G.V., Dias, R.J.: A Modified Fractal Transformation to Improve the Quality of Fractal Coded Images. In: IEEE Signal Processing Society 1998 International Conference on Image Processing, pp. 756–759. IEEE Computer Society Press, Los Alamitos (1998)
Fisher, Y.: Fractal Image Compression: Theory and Application. Springer, New York (1994)
Kominek, J.: Waterloo BragZone and Fractals Repository (January 25, 2007), http://links.uwaterloo.ca/bragzone.base.html
Recommendation ITU-R BT-500-11 Methodology for the subjective assessment of the quality of television pictures, Geneva (2000)
Nill, N.B.: A visual model weighted cosine transform for image compression and quality assessment. IEEE Trans. Commun. 3(6), 551–557 (1985)
Distasi, R., Nappi, M., Riccio, D.: A Range/Domain Approximation Error Based Approach for Fractal Image Compression. IEEE Transaction on Image Processing 15(1), 89–97 (2006)
Starosolski, R.: Performance evaluation of lossless medical and natural continuous tone image compression algorithms. In: Proceedings of the SPIE Conference, vol. 59, pp. 116–127 (2005), http://sun.iinf.polsl.gliwice.pl/~rstaros/mednat/index.html
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Abate, A., Nappi, M., Riccio, D. (2007). Embedding Quality Measures in PIFS Fractal Coding. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_70
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DOI: https://doi.org/10.1007/978-3-540-74260-9_70
Publisher Name: Springer, Berlin, Heidelberg
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