DocumentCode
2027055
Title
A low complexity multiresolution approach to image compression using pruned nested tree-structured vector quantization
Author
Perlmutter, Sharon M. ; Gray, Robert M.
Author_Institution
Inf. Syst. Lab., Stanford Univ., CA, USA
Volume
1
fYear
1994
fDate
13-16 Nov 1994
Firstpage
588
Abstract
A novel algorithm is described for constructing a progressive, multiresolution compression code. The codec consists of nested levels of tree-structured vector quantizers (TSVQs) where the codebook for each level of the nested TSVQs is constructed from the terminal leaves of the TSVQ from the previous level. In order to generate a multiresolution output in a progressive manner, the codeword dimension at each level´s TSVQ is greater than or equal to those of the previous levels. Pruning is performed on the nested TSVQs to achieve the bit allocation across the levels. The resulting pruned TSVQ provides a multiresolution output with low computational complexity at the decoder while simultaneously providing superior performance to ordinary pruned TSVQ at low bit rates
Keywords
computational complexity; image coding; image resolution; tree data structures; vector quantisation; TSVQ; bit allocation; codebook; codec; codeword dimension; computational complexity; decoder; image compression; low bit rates; low complexity multiresolution approach; multiresolution output; nested levels; performance; progressive multiresolution compression code; pruned nested tree-structured vector quantization; pruning; terminal leaves; tree-structured vector quantizers; Bit rate; Codecs; Computational complexity; Decoding; Image coding; Image resolution; Information systems; Quantization; Spatial resolution; Table lookup;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location
Austin, TX
Print_ISBN
0-8186-6952-7
Type
conf
DOI
10.1109/ICIP.1994.413382
Filename
413382
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