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Entropy-coded pyramid vector quantisation for interband wavelet image coding

熵编码的带间小波编码图像金字塔矢量量化

作     者:Vij, M Kingsbury, N 

作者机构:Silicon & Software Syst Dublin 18 Ireland Univ Cambridge Dept Engn Cambridge CB2 1PZ England 

出 版 物:《IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING》 (IEE Proc Vision Image Signal Proc)

年 卷 期:2000年第147卷第4期

页      面:304-312页

核心收录:

主  题:.image coding lattices sub-band interband quantisation lattice points quantisers entropy codes 

摘      要:Novel class-based entropy coding algorithms for lattice quantised hierarchical (or interband) vectors are presented. The vectors an formed from wavelet coefficients on different scales from similarly oriented sub-bands corresponding to the same spatial location. Structures have been designed specifically for interband vectors drawn from wavelet coefficients, where large groups of approximately equiprobable lattice points are grouped into relatively few classes, known as sub-classes, super-classes and super-super-classes, enabling accurate probability estimates from training data to be obtained for entropy coding of the class indices. Further, it has been found that the best quantiser is a combination of the Z(n) and D-n lattices which has been termed an augmented lattice. The performance of the method, entitled entropy-coded pyramid vector quantisation (ECPVQ), is evaluated on real images and the results show that ECPVQ is competitive, particularly at low bit-rates, with current state-of-the-art wavelet-based coders. A subjective comparison with current high performance scalar quantisation based coders shows that ECPVQ is likely to better preserve fine texture detail in the decoded images because of the finer quantisation of low energy wavelet coefficients that occurs with the augmented lattice.

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