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Proceedings Paper

Image encoding using chaotic maps and strange attractors
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Paper Abstract

We describe an application of nonlinear dynamical systems to image transformation and encoding. Our approach is different from the classical one where affine discrete maps are used. Similarly to classical fractal image compression, nonlinear maps use the redundancy in the image for compression. Furthermore, compression speed is enhanced whenever nonlinear maps have more than one attractor. Nonlinear maps having strange chaotic attractors can also be used to encode the image. In this case, the image will take the shape of the strange attractor when mapped under the nonlinear system. The procedure needs some precautions for chaotic maps, because of the sensitivity to initial conditions. Another possibility is to use strange attractors to hide the initial image using various schemes. For example, it is possible to hide the image using position permutation, value permutation, or both position and value permutations. We develop an algorithm to show that chaotic maps can be used successfully for this purpose. We also show that the sensitivity to initial conditions of chaotic maps forms the basis of the encryption strategy.

Paper Details

Date Published: 28 May 2003
PDF: 8 pages
Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); doi: 10.1117/12.473062
Show Author Affiliations
Fethi Belkhouche, Tulane Univ. (United States)
Uvais Qidwai, Tulane Univ. (United States)

Published in SPIE Proceedings Vol. 5014:
Image Processing: Algorithms and Systems II
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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