An IFS (Iterated Function System) using contractions can generate complex images by simple computation. For image representation by an IFS, it is necessary to solve an inverse problem, that is, to find functions providing invariant sets of an IFS. However, it is unclear how to find such functions and how natural images can be represented as invariant sets of an IFS. In the biginning of this paper, we propose a local parallel random IFS algorithm for generationg fractal images, which is suitable for parallel computers. Next, we propose a method to determine an IFS, consisting of affine contractions and associated propabilities, for an image block, using minimum square error criteria. Using this method, the IFS estimation and reconstruction characteristics are evaluated from the view point of signal-to-noise ratio. We also propose an adaptive method for local IFS estimation, which satisfies the condition of given permissible error. It is shown that the proposed method improves both representation effiency and signal-to-noise ratio compared to those of the fixed method.
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