Hierarchical vector quantization of perceptually weighted block transforms

This paper presents techniques for the design of generic block transform based vector quantizer encoders implemented by table lookups. In these table lookup encoders, input vectors to the encoders are used directly as addresses in code tables to choose the codewords. There is no need to perform the forward or reverse transforms. They are implemented in the tables. In order to preserve manageable table sizes for large dimension VQ´s, we use hierarchical structures to quantize the vector successively in stages. Since both the encoder and decoder are implemented by table lookups, there are no arithmetic computations required in the final system implementation. The algorithms are a novel combination of any generic block transform (DCT, Haar, WHT) and hierarchical vector quantization. They use perceptual weighting and subjective distortion measures in the design of VQ´s. They are unique in that both the encoder and the decoder are implemented with only table lookups and are amenable to efficient software and hardware solutions