Image Compression by Redundancy Reduction

  • Carlos Magno Sousa
  • André Borges Cavalcante
  • Denner Guilhon
  • Allan Kardec Barros
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4666)

Abstract

Image compression is achieved by reducing redundancy between neighboring pixels but preserving features such as edges and contours of the original image. Deterministic and statistical models are usually employed to reduce redundancy. Compression methods that use statistics have heavily been influenced by neuroscience research. In this work, we propose an image compression system based on the efficient coding concept derived from neural information processing models. The system performance is compared with principal component analysis (PCA) and the discrete cosine transform (DCT) at several compression ratios (CR). Evaluation through both visual inspection and objective measurements showed that the proposed system is more robust to distortions such as ringing and block artifacts than PCA and DCT.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kortamnl, C.M.: Redundancy Reduction-A Practical Method of Data Compression. Proc. of the IEEE 55(3), 223–226 (1967)Google Scholar
  2. 2.
    Barros, A.K., Chichocki, A.: Neural Coding by Redundancy Reduction and Correlation. In: Proc. of the VII Brazilian Symposium on Neural Networks (SBRN) (IEEE) (2002)Google Scholar
  3. 3.
    Ahmed, N., Natarajan, T., Rao, K.R.: Discrete Cosine Transform. IEEE Trans. Computers, 90–93 (1974)Google Scholar
  4. 4.
    Wallace, G.K.: The JPEG still-picture compression standard. Commun. ACM 34, 30–44 (1991)CrossRefGoogle Scholar
  5. 5.
    Gibbs, J.W.: Fourier Series. Nature, 59 (1898)Google Scholar
  6. 6.
    Coudoux, F.X., Gazalet, M.G., Corlay, P., Rouvaen, J.M.: A Perceptual Approach to the Reduction of Blocking Effect in DCT-Coded Images. Journal of Visual Com- munication and Image Representation 8(4), 327–337 (1997)CrossRefGoogle Scholar
  7. 7.
    Simoncelli, E.P., Olshausen, B.A.: Natural Image statistics and Neural Representation. Annu. Rev. Neurosci., 1193–216 (2001)Google Scholar
  8. 8.
    Dony, R.D., Haykin, S.: Proc. of IEEE Neural Network Approaches to Image Compression, vol. 83(2), pp. 288–303 (1995)Google Scholar
  9. 9.
    Ferreira, A.J, Figueiredo, M.A.T.: On the use of independent component analysis for image compression. Signal Processing: Image Communication 21, 378–389 (2006)CrossRefGoogle Scholar
  10. 10.
    Guilhon, D., Barros, A.K.: ECG Compression by Efficient Coding. In: ICA (submitted, 2007)Google Scholar
  11. 11.
    Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley and Sons, New York (2001)Google Scholar
  12. 12.
    Mallat, S., Zhang, Z.: Matching pursuit with time-frequency dictionaries. IEEE Transactions on Signal Processing 41(12), 3397–3415 (1993)MATHCrossRefGoogle Scholar
  13. 13.
    Martinez, A.M., Benavente, R.: The AR Face Database. CVC Technical Report, vol. 24 (1998)Google Scholar
  14. 14.
    Lloyd, S.P.: Least Squares Quantization in PCM. IEEE Transactions on Information Theory IT-28, 129–137 (1982)CrossRefMathSciNetGoogle Scholar
  15. 15.
    Huffman, D.A.: A method for the construction of minimum-redundancy codes. In: Proceedings of the I.R.E. pp. 1098–1102 (1952)Google Scholar
  16. 16.
    Miyahara, M., Kotani, K., Algazi, V.: Objective picture quality scale (pqs) for image coding. IEEE Trans. Commun 46, 1215–1226 (1998)CrossRefGoogle Scholar
  17. 17.
    Mannos, J.L., Sakrison, D.J.: The Effects of a Visual Fidelity Criterion on the Encoding of Images. IEEE Trans. on Information Theory it-20, 525–536 (1974)CrossRefGoogle Scholar
  18. 18.
    Ziou, D., Tabbone, S.: Edge Detection Techniques - An Overview. International Journal of Pattern Recognition and Image Analysis 8, 537–559 (1998)Google Scholar
  19. 19.
    Strijm, J., Cosmanb, P.C.: Medical image compression with lossless regions of interest. Signal Processing 59, 155–171 (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Carlos Magno Sousa
  • André Borges Cavalcante
  • Denner Guilhon
  • Allan Kardec Barros

There are no affiliations available

Personalised recommendations