An extension of entropy-constrained residual vector quantization is presented where inter-vector dependencies are exploited. The method, which the authors call conditional entropy-constrained residual vector quantization, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. The complexity of the proposed design algorithm is relatively low, due mainly to the efficiency of the multistage structure of the residual vector quantizer, but also to the effectiveness of the searching techniques used to locate the best conditioning spatial-stage region of support. Experimental results show that the new method outperforms standard entropy-constrained residual vector quantization while also requiring lower encoding complexity and memory requirements.<>
Image coding using high-order conditional entropy-constrained residual VQ
Proceedings of 1st International Conference on Image Processing ; 1 ; 613-617 vol.1
1994-01-01
407929 byte
Conference paper
Electronic Resource
English
Image Coding using High-Order Conditional Entropy-Constrained Residual VQ
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