Fast Full-Search Equivalent Nearest-Neighbor Search Algorithm
نویسنده
چکیده
A Fundamental activity in vector quantization involves searching a set of n kdimensional data to find the nearest one. We present a fast algorithm that is full-search equivalent, i.e. the match is as good as the one that could be found using exhaustive search. The proposed method utilizes law of cosines to calculate an estimate for distance, which is used to reduce the search area. Experiments show that the proposed algorithm outperforms the exhaustive search. Index Terms – image compression, fast nearest-neighbor search, vector quantization, hyper-spectral images.
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