Tree-structured product-codebook vector quantization

摘要

To carry out vector quantization (VQ) on large vectors, and hence obtain a good performance, it is necessary to introduce some structural constraint in the encoder. Product-codebook VQ reduces memory storage and encoding complexity. Tree-structured VQ reduces encoding complexity as well, and allows for progressive transmission. In this paper tree-structured product-codebook VQ is proposed to carry out low-complexity, low-memory storage VQ, with progressive transmission. The joint design of the tree-structured component codebooks is analyzed and a low-complexity greedy procedure is devised. The proposed approach has been implemented for two applications: the compression of gray-scale images, and the compression of multispectral images by means of the SPIHT algorithm, providing in both cases satisfactory experimental results.