Abstract
A new fast search algorithm for vector quantisation using the weight of image vectors is proposed. The codevectors are sorted according to their weights, and the search for the codevector having the minimum Euclidean-distance to a given input vector starts with the one having the minimum weight-distance, making use of the observation that the two codevectors are close to each other in most real images. The search is then made to terminate as soon as a simple yet novel test reports that any remaining vector in the codebook should have a larger Euclidean distance. Simulations show that the number of calculations can be reduced by up to four times the number achieved by the well known partial distance method.
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