Abstract
Fractal coding is an efficient method of image compression but has a major drawback: the very slow compression phase, due to a time-consuming similarity search between image blocks. A general acceleration method based on feature vectors is described, of which we can find many instances in the literature. This general method is then optimized using the well-known Karhunen-Loeve expansion, allowing optimal - in a sense to be defined - dimensionality reduction of the search space. Finally, a simple and fast search algorithm is designed, based on orthogonal range searching and avoiding the “curse of dimensionality” problem of classical best match search methods.
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© 1999 Springer-Verlag London Limited
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Cardinal, J. (1999). Faster Fractal Image Coding Using Similarity Search in a KL-transformed Feature Space. In: Dekking, M., Véhel, J.L., Lutton, E., Tricot, C. (eds) Fractals. Springer, London. https://doi.org/10.1007/978-1-4471-0873-3_19
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DOI: https://doi.org/10.1007/978-1-4471-0873-3_19
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