DocumentCode :
1641752
Title :
Coding of image textures using wavelet decomposition and hierarchical multirate vector quantization
Author :
Martens, Renée L J ; Venetsanopoulos, A.N. ; Hatzinakos, D.
Author_Institution :
Dept. of Electr. Eng., Toronto Univ., Ont., Canada
fYear :
1992
Firstpage :
101
Lastpage :
104
Abstract :
A preliminary investigation into the compression of texture images using wavelet decomposition and hierarchical multirate vector quantization (HMVQ) (of the high frequency subimages) is presented. The effect of using HMVQ on the first three multiresolution subimages of forty texture images is examined. When using unique codebooks for each image, even with the same codebook size the smoother images are decoded with higher quality results. The effects of using two different training sets to create codebooks is examined. It is found that the choice of the training set determines the effect of the coding on the texture images
Keywords :
data compression; image coding; image texture; vector quantisation; wavelet transforms; HMVQ; codebook; codebooks; hierarchical multirate vector quantization; high frequency subimages; image coding; image compression; image textures; multiresolution subimages; training sets; wavelet decomposition; Bit rate; Decoding; Filters; Image coding; Image reconstruction; Image resolution; Laplace equations; Signal resolution; Spatial resolution; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0805-0
Type :
conf
DOI :
10.1109/TFTSA.1992.274225
Filename :
274225
Link To Document :
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