Fractal Compression of Images with Projected IFS

Abstract : Standard fractal image compression, proposed by Jacquin, is based on IFS (Iterated Function Systems) defined in R². This modelization implies restrictions in the set of images being able to be compressed. These images have to be self similar in R². We propose a new model, the projected IFS, to approximate and code grey level images. This model has the ability to define affine IFS in a high dimension space, and to project it through control points, resulting in a non strictly self similar object in R². We proposed a method for approximating curves with such a model. In this paper, we extend the model capabilities to surfaces and images. This includes the combination of projected IFS in a quadtree structure and a complete coding scheme. First results show that our method gives better results than standard fractal image compression. Furthermore, in the very low bitrate context, the distortion/rate performances are equivalent to those obtained with EZW algorithm.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01581315
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Submitted on : Monday, September 4, 2017 - 3:01:08 PM
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  • HAL Id : hal-01581315, version 1

Citation

Eric Guérin, Eric Tosan, Atilla Baskurt. Fractal Compression of Images with Projected IFS. Int. Picture Coding Symposium, PCS'03, Saint-Malo, France, 2003., Apr 2003, Saint Malo, France. ⟨hal-01581315⟩

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