An efficient computation of Euclidean distances using approximated look-up table

For fast vector quantization (VQ) encoding, we present in this paper a new method to speed up the calculation of the squared Euclidean distance between two vectors. We call it the approximated look-up table (ALUT) method. This method considers the frequency of each squared number that occurs in the equation of squared Euclidean distances, and generates a more practical table to store squared numbers. ALUT makes use of this table and some simple operations to speed up the calculation of squared Euclidean distances. From the VQ simulation results, we see that ALUT saves memory and produces better image quality compared with some other methods. It is a suitable method for VLSI implementation