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
Index compressed tree-structured vector quantisation
โ Scribed by J. Shanbehzadeh; P.O. Ogunbona
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 587 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0923-5965
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper introduces a novel coding scheme based on Tree-Structured Vector Quantisation (TSVQ) scheme for image compression. The genealogical relationship among the indices of the neighbouring blocks generated from vector quantisation is exploited to improve the coding performance of TSVQ. The proposed coding scheme provides about 3.5 dB improvement over the basic TSVQ scheme and outperforms VQ schemes with memory and JPEG coding standard at low bit-rates. In addition its performance is comparable with address VQ but with much less complexity.
๐ SIMILAR VOLUMES
We describe some new methods for constructing discrete acoustic phonetic hidden Markov models (HMMs) using tree quantizers having very large numbers (16-64 K) of leaf nodes and tree-structured smoothing techniques. We consider two criteria for constructing tree quantizers (minimum distortion and min