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Best Achievable Compression Ratio for Lossy Image Coding

  • Jose A. García
  • Joaquin Fdez-Valdivia
  • Rosa Rodriguez-Sánchez
  • Xose R. Fdez-Vidal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2652)

Abstract

The trade-off between image fidelity and coding rate is reached with several techniques, but all of them require an ability to measure distortion. The problem is that finding a general enough measure of perceptual quality has proven to be an elusive goal. Here, we propose a novel technique for deriving an optimal compression ratio for lossy coding based on the relationship between information theory and the problem of testing hypotheses. As an example of the proposed technique, we analyze the effects of lossy compression at the best achievable compression ratio on the identification of breast cancer microcalcifications.

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References

  1. 1.
    Cover, T., Thomas, J.: Elements of Information Theory. Wiley Series in Telecommunications. John Wiley and Sons, Inc., Chichester (1991)zbMATHCrossRefGoogle Scholar
  2. 2.
    Egger, O., Fleury, P., Ebrahimi, T., Kunt, M.: High-performance compression of visual information–A Tutorial Review–Part I: Still Pictures. Proceedings of the IEEE 87(6), 976–1013 (1999)CrossRefGoogle Scholar
  3. 3.
    Garcia, J.A., Fdez-Valdivia, J., Fdez-Vidal, X.R., Rodriguez-Sanchez, R.: Best achievable compression ratio for lossy image coding, Technical report, Department of Computer Science and Artificial Intelligence, University of Granada, Spain (2002), avalaible in ftp://decsai.ugr.es/pub/diata/techrep/TR990324.ps.Z
  4. 4.
    Karssemeijer, N.: Adaptive noise equalization and image analysis in mammography. In: 13th Int. Conf. Inform. Processing Med. Imag., pp. 472–486 (1992)Google Scholar
  5. 5.
    Kullback, S.: Information theory and statistics. Gloucester, Peter Smith (1978)Google Scholar
  6. 6.
    Ortega, A., Ramchandran, K.: Rate-distortion methods for image and video compression. IEEE Signal processing magazine 4, 23–50 (1998)CrossRefGoogle Scholar
  7. 7.
    Said, A., Pearlman, W.A.: A new fast and efficient image coder based on set partitioning in hierarchical trees. IEEE Trans. on Circuits and Systems for Video Technology 6, 243–250 (1996)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jose A. García
    • 1
  • Joaquin Fdez-Valdivia
    • 1
  • Rosa Rodriguez-Sánchez
    • 1
  • Xose R. Fdez-Vidal
    • 2
  1. 1.Depto. Ciencias de la Computación e I.A.E.T.S. de Ingeniería Informática, Univ. de GranadaGranadaSpain
  2. 2.Depto. Física Aplicada. Facultad de FísicaUniv. de. Santiago de CompostelaSantiago de CompostelaSpain

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