Abstract
This paper proposes a vector quantization using wavelet transform and enhanced SOM algorithm for color image compression. To improve the defects of SOM algorithm, we propose the enhanced self-organizing algorithm, which, at first, reflects the error between the winner node and the input vector in the weight adaptation by using the frequency of the winner node, and secondly, adjusts the weight in proportion to the present weight change and the previous weight one as well. To reduce the blocking effect and improve the resolution, we construct vectors by using wavelet transform and apply the enhanced SOM algorithm to them. The simulation results show that the proposed method energizes the compression ratio and decompression ratio.
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© 2004 Springer-Verlag Berlin Heidelberg
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Kim, K.B., Kim, D.S. (2004). Color Image Vector Quantization Using Wavelet Transform and Enhanced Self-organizing Neural Network. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_24
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DOI: https://doi.org/10.1007/978-3-540-30499-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23931-4
Online ISBN: 978-3-540-30499-9
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