Abstract
In this paper we present a new theoretical approach to the problem of optimal Vector Quantization. We base, in fact, our method on the a priori explicit analysis of the effects on the MSE distortion introduced by an arbitrary exchange of training vectors among clusters. Even when the theoretical results corresponding to the simplest possible case are used, the proposed algorithm outperforms the GLA method to an impressive extent both in speed and in performance. Experiments on different images from the USC database have proved that the proposed algorithm is 5 to 10 times faster than the GLA method increasing the convergence Peak Signal to Noise Ratio (PSNR) of up to 1.12 dB.
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© 1995 Springer-Verlag Berlin Heidelberg
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Braccini, C., Cocurullo, F., Lavagetto, F. (1995). A fast algorithm for high quality vector quantization codebook design. In: Braccini, C., DeFloriani, L., Vernazza, G. (eds) Image Analysis and Processing. ICIAP 1995. Lecture Notes in Computer Science, vol 974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60298-4_326
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DOI: https://doi.org/10.1007/3-540-60298-4_326
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