Abstract
We introduce new techniques to generate real-world images. Many of the natural images exhibit a hierarchical structure and a balanced combination of both order and chaos. We show how a controlled use of deterministic chaos yields a powerful method to concisely describe and to efficiently generate complex realistic images. The basic technique is the use of mutually recursive function systems (MRFS) possibly with additional control on the order of computations. Then we show that, surprisingly, regular sets of control sequences are convenient but not essential. Some examples are presented illustrating the power of the technique. It is also shown that the images generated by uniformly growing L-systems can be more effectively generated by MRFS, and that every L-system can be simulated if we use a control set produced by an iterative GSM.
Extended Abstract
This research was supported by the National Sciences Foundation under Grant No. CCR-8702752.
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Culik, K., Dube, S. (1991). Balancing order and chaos in image generation. In: Albert, J.L., Monien, B., Artalejo, M.R. (eds) Automata, Languages and Programming. ICALP 1991. Lecture Notes in Computer Science, vol 510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54233-7_167
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DOI: https://doi.org/10.1007/3-540-54233-7_167
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