Tree-structured vector quantization with significance map for wavelet image coding

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Data Compression Conference (DCC '95)

Snowbird, Utah

March 28-March 30

ISBN: 0-8186-7012-6

	ASCII Text	x
	P.C. Cosman, S.M. Perlmutter, K.O. Perlmutter, "Tree-structured vector quantization with significance map for wavelet image coding," Data Compression Conference, pp. 33, Data Compression Conference (DCC '95), 1995.

	BibTex	x
	@article{ 10.1109/DCC.1995.515493, author = {P.C. Cosman and S.M. Perlmutter and K.O. Perlmutter}, title = {Tree-structured vector quantization with significance map for wavelet image coding}, journal ={Data Compression Conference}, volume = {0}, year = {1995}, isbn = {0-8186-7012-6}, pages = {33}, doi = {http://doi.ieeecomputersociety.org/10.1109/DCC.1995.515493}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Compression Conference TI - Tree-structured vector quantization with significance map for wavelet image coding SN - 0-8186-7012-6 SP EP A1 - P.C. Cosman, A1 - S.M. Perlmutter, A1 - K.O. Perlmutter, PY - 1995 KW - tree data structures; vector quantisation; wavelet transforms; transform coding; image coding; rate distortion theory; tree-structured vector quantization; significance map; wavelet image coding; variable-rate tree-structured VQ; orthogonal wavelet decomposition; spatially corresponding vectors; higher subbands; side information; algorithm; distortion/rate tradeoff; test image; PSNR VL - 0 JA - Data Compression Conference ER -

P.C. Cosman, Minnesota Univ., Minneapolis, MN, USA

S.M. Perlmutter, Minnesota Univ., Minneapolis, MN, USA

K.O. Perlmutter, Minnesota Univ., Minneapolis, MN, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DCC.1995.515493

Variable-rate tree-structured VQ is applied to the coefficients obtained from an orthogonal wavelet decomposition. After encoding a vector, we examine the spatially corresponding vectors in the higher subbands to see whether or not they are "significant", that is, above some threshold. One bit of side information is sent to the decoder to inform it of the result. When the higher bands are encoded, those vectors which were earlier marked as insignificant are not coded. An improved version of the algorithm makes the decision not to code vectors from the higher bands based on a distortion/rate tradeoff rather than a strict thresholding criterion. Results of this method on the test image "Lena" yielded a PSNR of 30.15 dB at 0.174 bits per pixel.

Index Terms:

tree data structures; vector quantisation; wavelet transforms; transform coding; image coding; rate distortion theory; tree-structured vector quantization; significance map; wavelet image coding; variable-rate tree-structured VQ; orthogonal wavelet decomposition; spatially corresponding vectors; higher subbands; side information; algorithm; distortion/rate tradeoff; test image; PSNR

Citation:

P.C. Cosman, S.M. Perlmutter, K.O. Perlmutter, "Tree-structured vector quantization with significance map for wavelet image coding," dcc, pp.33, Data Compression Conference (DCC '95), 1995

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