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Image Compression Algorithm Based on Morphological Associative Memories

  • Enrique Guzmán
  • Oleksiy Pogrebnyak
  • Cornelio Yáñez
  • José A. Moreno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)

Abstract

A new method for image compression based on Morphological Associative Memories (MAM) is proposed. We used MAM at the transformation stage of image coding, thereby replacing the traditional methods such as Discrete Cosine Transform or Wavelet Transform. After applying the MAM, the informative image data are concentrated in a minimum of values. The next stages of image coding can be obtained by taking advantage of this new representation of the image. The main advantage offered by the MAM with respect to the traditional methods is the speed of processing, whereas the compression rate and the obtained signal to noise ratios compete with the traditional methods.

Keywords

Image compression Morphological Associative Memories Morphological Hetroassociative Memories min 

References

  1. 1.
    Ahmed, N., Natrajan, T., Rao, K.R.: Discrete Cosine Transform. IEEE Transactions on Computer 23, 90–93 (1974)zbMATHCrossRefGoogle Scholar
  2. 2.
    Chen, W.H., Smith, C.H., Fralick, S.C.: A Fast Computational Algorithm for the Discrete Cosine Transform. IEEE Transactions on Communications COM-25, 1004–1009 (1977)CrossRefGoogle Scholar
  3. 3.
    Arai, Y., Agui y, T., Nakajima, M.: A Fast DCT-SQ Scheme for Image. Transactions of the IEICE E71(11), 1095–1097 (1988)Google Scholar
  4. 4.
    Tseng, B.D., Miller, W.C.: On Computing the Discrete Cosine Transform. IEEE Transactions on Computer C-27(10), 966–968 (1978)CrossRefGoogle Scholar
  5. 5.
    Winograd, S.: On Computing the Discrete Fourier Transform. Proceedings of the National Academy of Sciences of the United States of America 73(4), 1005–1006 (1976)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Wallace, G.K.: The JPEG Still Picture Compression Standard. Communications of the ACM 34(4), 30–44 (1991)CrossRefGoogle Scholar
  7. 7.
    ISO, Digital compression and coding of continuous-tone still images: Requirements and guidelines, ISO/IEC IS 10918-1 (1994) Google Scholar
  8. 8.
    DeVore, R.A., Jawerth, B., Lucier, B.J.: Image Compression Through Wavelet Transform Coding. IEEE Transactions on Information Theory 38(2), 719–746 (1992)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Antonini, M., Barlaud, M., Mathieu, P., Daubechies, I.: Image Coding Using Wavelet Transform. IEEE Transactions on Image Processing 1(2), 205–220 (1992)CrossRefGoogle Scholar
  10. 10.
    Lewis, A.S., Knowles, G.: Image Compression Using the 2-D Wavelet Transform. IEEE Transactions on Image Processing 1(2), 244–250 (1992)CrossRefGoogle Scholar
  11. 11.
    Shapiro, J.M.: Embedded Image Coding Using Zerotrees of Wavelet Coefficients. IEEE Transactions on Signal Processing 41(12), 3445–3462 (1993)zbMATHCrossRefGoogle Scholar
  12. 12.
    Said, A., Pearlman, W.A.: A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees. IEEE Transactions on Circuits and Systems for Video Technology 6(3), 243–250 (1996)CrossRefGoogle Scholar
  13. 13.
    Taubman, D.: High Performance Scalable Image Compression with EBCOT. IEEE Transactions on Image Processing 9(7), 1158–1170 (2000)CrossRefGoogle Scholar
  14. 14.
    Joint Photographic Experts Group. JPEG 2000 Part I Final Committee Draft Version 1.0 ISO/IEC JTC 1/SC 29/WG 1, N1646R (ITU-T SG8) (2000)Google Scholar
  15. 15.
    Ritter, G.X., Sussner, P., Díaz de León, J.L.: Morphological Associative Memories. IEEE Transactions on Neural Networks 9(2), 281–293 (1998)CrossRefGoogle Scholar
  16. 16.
    Hopfield, J.J.: Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proceedings of the National Academy of Sciences of the USA 79, 2554–2558 (1982)CrossRefMathSciNetGoogle Scholar
  17. 17.
    Castellanos, C., De León, y.J.L.D., Sánchez, A.: Análisis Experimental con las Memorias Asociativas Morfológicas. In: XXI Congreso Internacional de Ingeniería Electrónica, Electro 1999, Instituto Tecnológico de Chihuahua, Chih., México, pp. 11–16 (1999)Google Scholar
  18. 18.
    Yáñes, C., Díaz de León, y.J.L.D.: Memorias Morfológicas Heteroasociativas. Centro de Investigación en Computación, IPN, México, IT 57, Serie Verde (2001) ISBN 970-18-6697-5Google Scholar
  19. 19.
    Yáñes, C., Díaz de León, y.J..L.: Memorias Morfológicas Autoasociativas. Centro de Investigación en Computación, IPN, México, IT 58, Serie Verde (2001) ISBN 970-18-6698-3Google Scholar
  20. 20.
    Ritter, G.X., Díaz de León, J.L., Sussner, P.: Morphological Bidirectional Associative Memories. Neural Networks 12(6), 851–867 (1999)CrossRefGoogle Scholar
  21. 21.
    Xiong, Z., Guleryuz, O.G., Orchard, M.T.: A DCT-Based Embedded Image Coder. IEEE Signal processing Letters 3(11), 289–290 (1996)CrossRefGoogle Scholar
  22. 22.
    Xiong, Z., Ramchandran, K., Orchard, M.T., Zhang, Y.: A Comparative Study of DCT- and Wavelet-Based Image Coding. IEEE Transactions on Circuits and Systems for Video Technology 9(5), 692–695 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Enrique Guzmán
    • 1
  • Oleksiy Pogrebnyak
    • 2
  • Cornelio Yáñez
    • 2
  • José A. Moreno
    • 1
  1. 1.Universidad Tecnológica de la Mixteca 
  2. 2.Centro de Investigación en Computación del Instituto Politécnico Nacional 

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