Adaptive Delaunay triangulation for attractor image coding

The principle of attractor image coding presented in this paper is based on the theory of IFS (iterated function systems). The algorithm exploits piece-wise similarities between block of different sizes. To improve the algorithms based on regular and square blocks, we propose an adaptive Delaunay triangulation of the image support. The originality of the method is to map the triangles on specific parts of the image in order to have lots of similarities between them.

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

[2]  Horst Bischof,et al.  Combining pyramidal and fractal image coding , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[3]  J. M. Chassery,et al.  Edge-region segmentation process based on generalized Voronoi diagram representation , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

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

[5]  J. Chassery,et al.  Segmentation and measurement based on 3D Voronoi diagram: application to confocal microscopy. , 1993, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[6]  D. F. Watson.  Computing the n-Dimensional Delaunay Tesselation with Application to Voronoi Polytopes , 1981, Comput. J..