DocumentCode
892604
Title
Adaptive entropy-coded pruned tree-structured predictive vector quantization of images
Author
Kim, Yong Han ; Modestino, James W.
Author_Institution
Dept. of Electr., Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Volume
41
Issue
1
fYear
1993
fDate
1/1/1993 12:00:00 AM
Firstpage
171
Lastpage
185
Abstract
Simpler versions of a previously introduced adaptive entropy-coded predictive vector quantization (PVQ) scheme where the embedded entropy constrained vector quantizer (ECVQ) is replaced by a pruned tree-structured VQ (PTSVQ) are described. The resulting encoding scheme is shown to result in drastically reduced complexity at only a small cost in performance. Coding results for selected real-world images are given
Keywords
entropy; filtering and prediction theory; image coding; trees (mathematics); vector quantisation; adaptive entropy-coded predictive vector quantization; encoding scheme; image coding; pruned tree-structured predictive vector quantization; Algorithm design and analysis; Buffer storage; Decoding; Feedback loop; Image coding; Image reconstruction; Image storage; Rate-distortion; Robustness; Vector quantization;
fLanguage
English
Journal_Title
Communications, IEEE Transactions on
Publisher
ieee
ISSN
0090-6778
Type
jour
DOI
10.1109/26.212377
Filename
212377
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