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Fractal Image Encoding and Analysis
In fractal image compression the encoding step is computationally expensive. A large number of sequential searches through a list of domains (portions of the image) are carried out while trying to find best matches for other image portions called ranges. Our theory developed here shows that this basic procedure of fractal image compression is equivalent to multi-dimensional nearest neighbor search in a space of feature vectors. This result is useful for accelerating the encoding procedure indoi:10.1007/978-3-662-03512-2_6 fatcat:t6to6p2fgvewris4b2tbqx7c5y