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Efficient near neighbor search (ENN-search) method for high dimensional data sets with noise

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A nearer neighbor matching and compression method and apparatus provide matching of data vectors to exemplar vectors. A data vector is compared to exemplar vectors contained within a subset of exemplar vectors, i.e., a set of possible exemplar vectors, to find a match. After a match is found, a probability function assigns a probability value based on the probability that a better matching exemplar vector exists. If the probability that a better match exists is greater than a predetermined probability value, the data vector is compared to an additional exemplar vector. If a match is not found, the data vector is added to the set of exemplar vectors. Data compression may be achieved in a hyperspectral image data vector set by replacing each observed data vector representing a respective spatial pixel by reference to a member of the exemplar set that “matches' the data vector. As such, each spatial pixel will be assigned to one of the exemplar vectors.

Palmadesso, Peter J.; Bowles, Jeffrey H.; Gillis, David B.
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IT and Software
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Grant time: 
1,271 days
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