A hashing-based scheme for organizing vector quantization codebook

One of the problems in vector quantization (VQ) is its relatively long encoding time especially when an exhaustive search is made for the codevector. This paper presents a hashing-based technique to organize the codebook so that the search time can be significantly reduced. Hashing gives the speed advantages of a direct search, while maintaining a codebook of reasonable size. Experiments show that hashing-based VQ sustained image quality as the encoding time was reduced, while full search VQ suffered greatly. For example, for 2×2 vectors and with 1024 codebook entries, encoding time was reduced by a factor of 10 without significant loss of image quality