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Color Image Vector Quantization Using Wavelet Transform and Enhanced Self-organizing Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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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References

  1. Rabbani, M., Jones, P.W.: Digital Image Compression Technique, pp. 144–169. Spie Optical Engineering Press (1991)

    Google Scholar 

  2. Orchard, M.T., Bouman, C.A.: Color Quantization of Images. IEEE Trans. On Sp 39(12), 2677–2690 (1991)

    Article  Google Scholar 

  3. Godfrey, K.R.L., Attikiouzel, Y.: Self-Organized Color Image Quantization for Color Image Data Compression. Proc. of ICNN 3, 1622–1626 (1993)

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  4. Gersho, A., Gray, R.M.: Vector Quantization and Signal Compression. Kluwer Academic Publishers, Dordrecht (1992)

    MATH  Google Scholar 

  5. Oehler, K.L., Gray, R.M.: Combining Image Compression and Classification using Vector Quantization. IEEE Multimedia, 36–45 (1997)

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  6. Kim, K.B., Cha, E.Y.: A Fuzzy Self-Organizing Vector Quantization For Image. Proc. of IIZUKA 2, 757–760 (1996)

    Google Scholar 

  7. Madeiro, F., Vilar, R.M., Fechine, J.M., Aguiar Neto, B.G.: A Slef-Organizing Algorithm for Vector Quantizer Design Applied to Signal Processing. Int. Journal of Neural Systems 9(3), 219–226 (1999)

    Article  Google Scholar 

  8. Strang, G., Nguyen, T.: Wavelets and Filter Banks. Wellesley-Cambridge Press (1996)

    Google Scholar 

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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

  • eBook Packages: Springer Book Archive

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