VQ bit rate reduction technique by transform compression

A technique to reduce the overhead of vector quantization (VQ) is developed. This method exploits the high correlation property among neighboring blocks. By rearranging the codebook after the training process, the indices of neighboring vectors have fewer varieties, then, the gains of compression is attained. For the energy compactness advantage of the discrete cosine transform (DCT), the indices buffer formed after the encoding phase are fed to the DCT to reduce the bit rate further. Statistics illustrators are addressed to prove the efficient performance of the proposed method. Experiments are carried out on natural gray images. Simulation results show that our method decreases the bit rate more than 50% with the same reconstructed image quality compared to standard VQ coding