Abstract
Weighted finite transducers (WFT) are finite state devices that serve as a powerful tool for describing and implementing a large variety of image transformations and more generally linear operators on real functions.Here we show new results on WFT and demonstrate that WFT are indeed an excellent tool for image manipulation and more generally for function transformation. We note that every WFA transformation is a linear operator and show that most of the interesting linear operators on real functions (on [0,1]2) can be easily implemented by WFT. They include affine transformations, low-pass or high-pass filters, wavelet transform, (partial) derivatives, simple and multiple integrals.KeywordsAffine TransformationFinite AutomatonHaar WaveletFinal DistributionImage TransformationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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