By B.G. Mertzios, P. Liatsis

The papers during this quantity specialize in the main smooth and significant features of photo and sign Processing and comparable parts that experience an important impression in our society. The papers should be labeled within the following 4 significant elements. Coding and Compression (image coding, picture subband, wavelet coding and illustration, video coding, movement estimation and multimedia); snapshot Processing and trend acceptance (image research, facet detection, segmentation, photo enhancement and recovery, adaptive platforms, color processing, trend and item popularity and classification); quickly Processing strategies (computational tools, VLSI DSP architectures); idea and purposes (identificiation and modelling, multirate clear out banks, wavelets in snapshot and sign processing, biomedical and business applications). The authors of those enormously high quality papers shape an enticing team, originating from the 5 continents, representing 33 international locations.

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C. K. al 'Competitive learning algorithms for vector quantization, Neural Networks, Vol. 3, pp 277-290, 1990. , Lee, T. 'Fuzzy competitive learning', Neural Networks, Vol. 7, No 3, pp 539-551, 1994. J. et al 'A VLSI neural processor for image data compression using self-organization networks' IEEE Trans. On Neural Networks, Vol. 3, 1992, No. 3, pp 506-519. D. M. 'An improvement of the minimum distortion encoding algorithm for vector quantization', IEEE Trans. , Vol Com-33, October 1985. K. G. Mertzios and P.

832, 29285 Brest Cedex #Technical University of Budapest, HUNGARY Department of Process Control, Budapest XI, Muegyetem rkp. 9, 1521 I. I n t r o d u c t i o n The most important task encountered in digital image transmission systems is image compression aiming at reducing the amount of information to be transmitted. The overall goal is to represent an image with the smallest possible amount of bits, and thereby, to speed up transmission and minimize storage requirements. In the past decade, a promising compression approach using vector quantization (VQ) [1-2] has received great attention.

Vol 4, pp. 228-235, 1994. [12] ISO International Standard 10918, Digital compression and coding of continuous-tone still images, Geneva 1994. 263, Video coding for narrow telecommunication channels at < 64kbit/s, April 1995. [14] E. Gotsman, Dynamic color quantization of video sequences, IEEE Trans. Vizualization and Computer Graphics, vol. 1, pp. 274-286, 1995. Godlove, Improved Color-Difference Formula, with Applications to Perceptibility and Acceptability of Fadings, J. Soc. K. G. Mertzios and P.

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