Color-image coding by an advanced vector-quantizer
Daniele Giusto, Gianni L. Vernazza · International Conference on Acoustics, Speech, and Signal Processing · 2002
An advanced vector quantizer for coding true-color images is presented. The starting point is the classical algorithm proposed by Y. Linde, A. Buzo, and A.M. Gray (LBG, 1980). On the basis of the LBG algorithm, a neural net able to furnish a starting codebook quite close to the optimal one is developed. As several vectors are infrequently used, a merge-and-split process has been performed to merge such vectors into adjacent ones, thus allowing free space to be reutilized to redistribute the most numerous partitions. Another aspect to be exploited is the existence of statistical redundancies between neighboring blocks. To sharply reduce the bit rate, an RGB predictor based on some transition matrices is developed. The basic idea of the development of an RGB predictor is provided by the address vector quantization (AVQ) technique. Results obtained by processing standard images are discussed.>