TY - JOUR
T1 - Pruned tree-structured vector quantization in image coding
AU - Riskin, Eve A.
AU - Daly, Elizabeth M.
AU - Gray, Robert M.
PY - 1989
Y1 - 1989
N2 - A recently developed technique for variable-rate vector quantizer (VQ) design has been applied to both memoryless and predictive VQ of images. This technique, called pruned tree-structured vector quantization (PTSVQ), uses variable-depth encoders that are tree-structured and thus have very low design and search complexity. PTSVQ is applied to a series of medical images, and gains over full-search VQ of up to 3.78 dB in the signal-to-noise-ratio (SNR) are measured. On still images from the USC database, gains of up to 1.63 dB in the peak SNR are realized for predictive PSTVQ over predictive full search VQ, resulting in high image quality at 0.51 bits per pixel.
AB - A recently developed technique for variable-rate vector quantizer (VQ) design has been applied to both memoryless and predictive VQ of images. This technique, called pruned tree-structured vector quantization (PTSVQ), uses variable-depth encoders that are tree-structured and thus have very low design and search complexity. PTSVQ is applied to a series of medical images, and gains over full-search VQ of up to 3.78 dB in the signal-to-noise-ratio (SNR) are measured. On still images from the USC database, gains of up to 1.63 dB in the peak SNR are realized for predictive PSTVQ over predictive full search VQ, resulting in high image quality at 0.51 bits per pixel.
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M3 - Conference article
AN - SCOPUS:0024901082
SN - 0736-7791
VL - 3
SP - 1735
EP - 1738
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
T2 - 1989 International Conference on Acoustics, Speech, and Signal Processing
Y2 - 23 May 1989 through 26 May 1989
ER -