EFFICIENT NEAR NEIGHBOR SEARCH (ENN-SEARCH) METHOD FOR HIGH DIMENSIONAL DATA SETS WITH NOISE

摘要

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 (18). After a match is found, a probability function assigns a probability value based on the probability that a better matching exemplar vector exists (22). 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 (24). 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 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 (26).