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Adaptive Fractal Image Sequence Coding by Variable Shape Decomposition

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Abstract

A two-phase fractal image sequence compression system is proposed. In the classification phase, according to the texture attribution a testing solid image block is assigned to its corresponding texture class. The texture attribution is derived from the tomographic block projection classification for the finite projection directions at the three-dimensional (3D) space. In the adaptive coding phase, both the algorithm of the 3D projection classification and the 3D variable shape decomposition are incorporated into the variable shape block transformation for image sequence. By applying this variable shape block transformation algorithm to fractal image sequence coding scheme, we can obtain a promising performance.

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References

  1. M. Kunt, M. Benard, and R. Leonardi, “Recent results in highcompression image coding,” IEEE Trans. Circuits and Systems, Vol. 34, No. 11, pp. 1306–1336, 1987.

    Google Scholar 

  2. M.F. Barnsley and A.D. Sloan, “A better way to compress images,” Byte Mag., Vol. 13, No. 1, pp. 215–224, 1988.

    Google Scholar 

  3. A.E. Jacquin, “Image coding based on a fractal theory of iterated contractive image transformations,” IEEE Trans. Image Process., Vol. 1, No. 1, pp. 18–30, 1992.

    Google Scholar 

  4. D.M. Monro and F. Dudbridge, “Fractal block coding of images,” Electronics Letters,Vol. 28, No. 11, pp. 1053–1055, 1992.

    Google Scholar 

  5. E.W. Jacobs, Y. Fisher, and R.D. Boss, “Image compression: A study of the iterated transform method,” Signal Process.,Vol. 29, No. 3, pp. 251–263, 1992.

    Google Scholar 

  6. H. Li, M. Novak, and R. Forchheimer, “Fractal-based image sequence compression scheme,” Optical Eng., Vol. 32, No. 7, pp. 1588–1595, 1993.

    Google Scholar 

  7. G. Lu, “Fractal image compression,” Signal Process.: Image Comm., Vol. 5, No. 4, pp. 327–343, 1993.

    Google Scholar 

  8. M.F. Barnsley, Fractals Everywhere, Academic: San Diego, CA, 1988.

    Google Scholar 

  9. B. Moghaddam, K.J. Hintz, and C.V. Stewart, “Fractal image compression and texture analysis,” in Proc. SPIE Conf. on Image Understanding, 1990, Vol. 1406, pp. 42–57.

    Google Scholar 

  10. A.E. Jacquin, “A novel fractal block-coding technique of digital images,” in Proc. IEEE Int. Conf. on Acoust., Speech, Signal Process., 1990, Vol. 4, pp. 2225–2228.

    Google Scholar 

  11. I.K. Kim and R.H. Park, “Still image coding based on vector quantization and fractal approximation,” IEEE Trans. Image Process., Vol. 5, No. 4, pp. 589–597, 1996.

    Google Scholar 

  12. D.M. Monro and F. Dudbridge, “A hybrid fractal transform,” in Proc. IEEE Int. Conf. on Acoust., Speech, Signal Process., 1993, Vol. 5, pp. 169–172.

    Google Scholar 

  13. S. Lepsoy, G.E. Oien, and T.A. Ramstad, “Attractor image compression with a fast noniterative decoding algorithm,” in Proc. IEEE Int. Conf. on Acoust., Speech, Signal Process., 1993, Vol. 5, pp. 337–340.

    Google Scholar 

  14. G. Vines and M.H. Hayes, “Adaptive IFS image coding with proximity maps,” in Proc. IEEE Int. Conf. on Acoust., Speech, Signal Process., 1993, Vol. 5, pp. 349–352.

    Google Scholar 

  15. L.C. Thomas and F. Deravi, “Pruning of the transform space in block-based fractal image compression,” in Proc. IEEE Int. Conf. on Acoust., Speech, Signal Process., 1993, Vol. 5, pp. 341–344.

    Google Scholar 

  16. C.J. Sze et al., “Fractal image coding system based on an adaptive side-coupling quadtree structure,” Image and Vision Computing, Vol. 14, No. 6, pp. 401–415, 1996.

    Google Scholar 

  17. R.A. Brooks and G. Dichiro, “Principles of computer assisted tomography (CAT) in radiographic and radioisotopic imaging,” Phys. Med. Biol., Vol. 21, pp. 689–732, 1976.

    Google Scholar 

  18. G.T. Herman, Image Reconstruction from Projections: The Fundamentals of Computerized Tomography, Academic Press: New York, 1980, pp. 60.

    Google Scholar 

  19. A. Macovski, Medical Imaging Systems, Prentice-Hall: Englewood Cliffs, NJ, 1983.

    Google Scholar 

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Chao, HC., Chieu, BC. Adaptive Fractal Image Sequence Coding by Variable Shape Decomposition. Journal of Mathematical Imaging and Vision 10, 269–279 (1999). https://doi.org/10.1023/A:1008335322964

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