J. Kominek. Convergence of fractal encoded images. In Proceedings DCC'95 Data Compression Conference, J. A. Storer, M. Cohn (eds.), March 1995.
Because fractal compression is highly asymmetric, most research to date has been devoted to improving compression performance [6,8,9]. Yet, it is the process of decompression that is most intriguing. Whether one uses the 'classical' approach originated by Barnsley [1] or the more practical method of Jacquin [5] that is considered here, an image is represented compactly in terms of an Iterated Function System (IFS). To recover this image the IFS is iterated, with each iteration bringing the process closer to the final result. To ensure convergence, Jacquin asserts that an IFS must be contractive and establishes a contractivity criterion. Jacobs, Fisher, and Boss found instead that an IFS may converge without being fully contractive, and introduce the idea of eventual contractivity [2]. Unfortunately, they provide but a rough guideline as to whether a fractal image will converge. Hurtgen offers a contractivity criterion in [3], but only for the highly restricted case of [7]. This paper examines convergence of fractal encoded images in greater detail.
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@InProceedings{Komi95b,
Author = {Kominek, J.},
Title = {Convergence of fractal encoded images},
BookTitle = {Proceedings DCC'95 Data Compression Conference},
editor = {Storer, J. A. and Cohn, M.},
Publisher = {IEEE Computer Society Press},
Month = {March},
Year = {1995}
}