A fast encoding algorithm for vector quantization based on Principal Component Analysis

For vector quantization (VQ), it is extremely time- consuming to extract the similar codeword with input vector during the encoding process. In this paper, we present an efficient algorithm to extract the features of input vector using Principal Component Analysis (PCA) and use these features to remove impossible codeword in the distortion computations stage. From the experimental results, it is shown that the proposed approach can largely decrease the computation time for achieving VQ coding with the same quality with full search algorithm. More specifically, compared with the DHSS algorithm, the proposed algorithm reduces the computational time by 0% to 39.46%. Compared with the Pan’s algorithm, the proposed algorithm reduces the computational time by 38.91% to 56.76%. Compared with the Lai’s algorithm, the proposed algorithm reduces the computational time by 15.79% to 36.36%.