DocumentCode :
1111301
Title :
A complexity reduction technique for image vector quantization
Author :
Chan, Chok-Ki ; Po, Lai-Man
Author_Institution :
Dept. of Electron. Eng., City Polytech. of Hong Kong, Hong Kong
Volume :
1
Issue :
3
fYear :
1992
fDate :
7/1/1992 12:00:00 AM
Firstpage :
312
Lastpage :
321
Abstract :
A technique for reducing the complexity of spatial-domain image vector quantization (VQ) is proposed. The conventional spatial domain distortion measure is replaced by a transform domain subspace distortion measure. Due to the energy compaction properties of image transforms, the dimensionality of the subspace distortion measure can be reduced drastically without significantly affecting the performance of the new quantizer. A modified LBG algorithm incorporating the new distortion measure is proposed. Unlike conventional transform domain VQ, the codevector dimension is not reduced and a better image quality is guaranteed. The performance and design considerations of a real-time image encoder using the techniques are investigated. Compared with spatial domain a speed up in both codebook design time and search time is obtained for mean residual VQ, and the size of fast RAM is reduced by a factor of four. Degradation of image quality is less than 0.4 dB in PSNR
Keywords :
data compression; encoding; picture processing; codebook design time; codevector dimension; complexity reduction; energy compaction properties; image quality; mean residual VQ; real-time image encoder; search time; spatial-domain image vector quantization; transform domain subspace distortion measure; Algorithm design and analysis; Cities and towns; Compaction; Degradation; Distortion measurement; Eigenvalues and eigenfunctions; Image coding; Image quality; Image storage; Vector quantization;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.148605
Filename :
148605
Link To Document :
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