Accelerating vector quantization of images using modified run length coding for adaptive block representation and difference measurement

In vector quantization (VQ) techniques, the block difference measurement in the nearest neighboring search and the iteration process in codebook generation are time consuming. Since there could be many smoothing or strongly related regions in images, the pixels values in the partitioned image blocks could be identical or quite similar. In this paper, two accelerating methods for codebook training and VQ coding based on the modified run-length coding method that can transform an image block into a coded vector (CV) are proposed. Acceleration can be achieved by measuring the distance between two CVs rather than measuring the difference between two image blocks. Computer simulation results show the proposed scheme outperforms the conventional VQ and the principal component analysis based methods in speeding up both the image coding and codebook training processes.