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A new fast nearest neighbor codeword search algorithm for image vector quantization (VQ) is introduced. This algorithm uses two significant features of a hadamard transformed vector, that is, the average, the variance, to eliminate more unmatched code words. It saves a great deal of computational time and distortion calculations. Experimental results demonstrate the performance of the proposed algorithm is good.