Scalable compression based on tree structured vector quantization of perceptually weighted block, lapped, and wavelet transforms
Navin Chaddha, Philip A. Chou, Tao Meng · Proceedings - International Conference on Image Processing · 2002
This paper presents an algorithm for scalable compression using tree structured vector quantization (TSVQ) of perceptually weighted block, lapped, or wavelet transforms. The algorithm produces an embedded bit-stream to support decoders with various spatial and temporal resolutions. Bandwidth scalability with a dynamic range from a few kbps to several Mbps is provided. The algorithm further supports decoders with varying alphabet size, computation, memory, latency and power requirements. The embedded bit-stream produced is prioritized with bits arranged in order of visual importance. The algorithm also allows easy joint-source channel coding on heterogenous networks. The subjective quality of compressed images improves significantly by the use of perceptual distortion measures.