Fractal Image Compression on a Pseudo Spiral Architecture

Fractal image compression is a relatively recent image compression method which exploits similarities in different parts of the image. The basic idea is to represent an image by fractals and each of which is the fixed point of an Iterated Function System (IFS). Therefore, an input image can be represented by a series of IFS codes rather than pixels. In this way, an impressive compression ratio 10000:1 can be achieved. The application of fractal image compression presented in this paper is based on a novel image structure, Spiral Architecture, which has hexagonal instead of square pixels as the basic element. In the paper evidence would suggest that introducing Spiral Architecture into fractal image compression will improve the compression performance in compression ratio with little suffering in image quality. There are also much research could be done in this area to further improve the results.

[1]  E. Kreyszig.  Introductory Functional Analysis With Applications , 1978 .

[2]  Eric L. Schwartz,et al.  Computational anatomy and functional architecture of striate cortex: A spatial mapping approach to perceptual coding , 1980, Vision Research.

[3]  M. Barnsley,et al.  Iterated function systems and the global construction of fractals , 1985, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[4]  Michael F. Barnsley,et al.  Fractals everywhere , 1988 .

[5]  Michael F. Barnsley,et al.  A better way to compress images , 1988 .

[6]  J. M. Beaumont.  Advances in block based fractal coding of still pictures , 1990 .

[7]  Arnaud E. Jacquin,et al.  Fractal image coding based on a theory of iterated contractive image transformations , 1990, Other Conferences.

[8]  A. Jacquin.  Fractal image coding: a review , 1993, Proc. IEEE.

[9]  Lyman P. Hurd,et al.  Fractal image compression , 1993 .

[10]  Jean-Bernard Martens,et al.  Estimation of edge parameters and image blur from local derivatives , 1994 .

[11]  Kaiser Uwe.  Adaptive Fractal Image Coding in the Frequency Domain , 1994 .

[12]  Donald M. Monro,et al.  Optimum parameters for hybrid fractal image coding , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[13]  Y. Fisher.  Fractal image compression: theory and application , 1995 .

[14]  Phillip Sheridan,et al.  Spiral architecture for machine vision , 1996 .

[15]  Scott E. Umbaugh,et al.  Computer Vision and Image Processing: A Practical Approach Using CVIPTools , 1997 .

[16]  Scott E. Umbaugh,et al.  Computer Vision and Image Processing: A Practical Approach Using Cviptools with Cdrom , 1997 .

[17]  Brendt Wohlberg,et al.  A review of the fractal image coding literature , 1999, IEEE Trans. Image Process..

[18]  Tom Hintz,et al.  Pseudo-invariant image transformations on a hexagonal lattice , 2000, Image Vis. Comput..

[19]  Qiang Wu,et al.  Virtual Spiral Architecture , 2004, PDPTA.