Abstract
The fractal image compression technique models a natural image using a contractive mapping called fractal mapping in the image space. In this chapter, we first introduce the concept of fractal mapping and some useful definitions. In Section 5.2, we demonstrate that the fractal image coding algorithm is compatible with other image coding methods. A new mapping in the image space, called partial fractal mapping is proposed in Section 5.3. A general framework of fractal-based hybrid image coding encoding/decoding systems is presented in Section 5.4. Section 5.5 proposes a new hybrid image coding scheme, which non-fractal coded regions are used to help the encoding of fractal coded regions. Experiments in Section 5.6 show that the proposed system performs better than the quadtree-based fractal image coding algorithm and the JPEG image compression standard at high compression ratios larger than 30.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
B.B. MandelbrotThe Fractal Geometry of NatureSan Francisco: W.H. Freeman, 1983.
M.F. BarnsleyFractals Everywhere, New York: Academic Press, 1988.
A.E. Jacquin, “Image coding based on a fractal theory of iterated contraceptive image transformations”IEEE Trans. Image Process.1(1): 18–30, Jan. 1992.
A.E. Jacquin, “Fractal image coding: a review”Proceedings of the IEEE81(10):1451–1465, Oct. 1993.
Y. Fisher, ed.Fractal Image Compression: Theory and ApplicationNew York: Springer-Verlag, 1994.
Y. Linde, A. Buzo, and R.M. Gray“ An algorithm for vector quantizer design”IEEE Trans. Commun.COM-28:84–95, Jan. 1980.
T. Laurencot and A.E. Jacquin, “Hybrid image block coders incorporating fractal coding and vector quantization, with a robust classification scheme”AT&T Tech. Memo. Feb. 1992.
G.E. Oien, and S. Lepsoy, “Fractal image coding with fast decoder convergence”Signal Processing40:105–117, 1994.
Y. Fisher, “Fractal image compression with quadtrees”, inFractal Image Compression: Theory and Applications to Digital ImagesY. Fisher, ed., New York: Springer-Verlag, 1994.
Z. Wang and Y.L. Yu, “Fractal block coding in residue domain,”China Journal of Electronics, 14(3):236–240, 1997.
X.K. Zhou, ed.Practical Microcomputer Image ProcessingBeijing: Beijing Univ. of Aeronautics and Astronautics Press, 1994.
I.H. Witten, R.M. Neal, and J.G. Cleary, “Arithmetic coding for data compression”Communications of the ACM30(6):520–540, Jun. 1987.
G.K. Wallace, The JPEG Still Picture Compression StandardCommunications of the ACM34(4):30–44, April 1991.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media New York
About this chapter
Cite this chapter
Zhang, D., Li, X., Liu, Z. (2001). Partial Fractal Model for Hybird Image Coding. In: Data Management and Internet Computing for Image/Pattern Analysis. The International Series on Asian Studies in Computer and Information Science, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1527-2_5
Download citation
DOI: https://doi.org/10.1007/978-1-4615-1527-2_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5598-4
Online ISBN: 978-1-4615-1527-2
eBook Packages: Springer Book Archive