Tree-structured vector quantization for progressive transmission image coding

We have reviewed the design and properties of tree-structured vector quantization (TSVQ) and its amenability to progressive transmission image coding systems. By optimally pruning a TSVQ to trade off average distortion for average rate, one obtains a variable rate (or variable length) tree-structured code. This encoder can send more (fewer) bits for more (less) active or important subblocks. The variable rate code can be used in a progressive transmission scheme by sending the first bit for each subblock codeword, then the second (if there is one), and so on. If lossy transmission is required, the VQ code can be followed by a noiseless coding of the residual error to eventually provide a perfect reproduction.

[1]  R. Gray,et al.  Speech coding based upon vector quantization , 1980, ICASSP.

[2]  R. Gray,et al.  Vector quantization , 1984, IEEE ASSP Magazine.

[3]  Allen Gersho,et al.  A fast codebook search algorithm for nearest-neighbor pattern matching , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  J. Makhoul,et al.  Vector quantization in speech coding , 1985, Proceedings of the IEEE.

[5]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[6]  K. Tzou Progressive Image Transmission: A Review And Comparison Of Techniques , 1987 .

[7]  L. Rabiner,et al.  The acoustics, speech, and signal processing society - A historical perspective , 1984, IEEE ASSP Magazine.

[8]  Philip A. Chou,et al.  Optimal pruning with applications to tree-structured source coding and modeling , 1989, IEEE Trans. Inf. Theory.