TY - GEN

T1 - Improved east encoding method of vector quantization based on dynamic element reordering for codewords

AU - Pan, Zhibin

AU - Kotani, Koji

AU - Ohmi, Tadahiro

PY - 2007

Y1 - 2007

N2 - Vector quantization (VQ) is a popular signal compression method. In a VQ framework, the encoding speed is one of the key issues for its practical applications. In principle, the high dimension of the original (n×n)-dimensional vectors is the reason that makes it is computationally very expensive to find the best-matched codeword for a given input vector by computing Euclidean distances. As a result, a lot of fast VQ encoding methods have been developed in the previous works based on using scalar statistical features (i.e., sum, variance or L2 norm) or lower dimensional multi-resolution representation (i.e., various pyramid data structures) of a vector to deal with this computational complexity problem caused by the high dimension of the original vectors. In particular, a very effective mixed-pyramid data structure is reported in the previous work [7], which features a minimum configuration by combining a 2-PM core sum pyramid and a (n×n)-PM auxiliary variance pyramid together. However, this mixed-pyramid failed to take the element order of a vector into account. In order to further improve the encoding performance of the previous work [7], this paper proposes to introduce a dynamic element reordering operation to let all elements of a codeword rearranged in an ascending order by an offline sorting process before it goes to construct the mixed-pyramid for the codeword. After the element reordering, it is possible to make the intermediate levels in the mixed-pyramid of a codeword keep more energy and become more powerful for rejection tests. Experimental results confirmed that the encoding efficiency of the proposed method remarkably outperforms the previous work [7].

AB - Vector quantization (VQ) is a popular signal compression method. In a VQ framework, the encoding speed is one of the key issues for its practical applications. In principle, the high dimension of the original (n×n)-dimensional vectors is the reason that makes it is computationally very expensive to find the best-matched codeword for a given input vector by computing Euclidean distances. As a result, a lot of fast VQ encoding methods have been developed in the previous works based on using scalar statistical features (i.e., sum, variance or L2 norm) or lower dimensional multi-resolution representation (i.e., various pyramid data structures) of a vector to deal with this computational complexity problem caused by the high dimension of the original vectors. In particular, a very effective mixed-pyramid data structure is reported in the previous work [7], which features a minimum configuration by combining a 2-PM core sum pyramid and a (n×n)-PM auxiliary variance pyramid together. However, this mixed-pyramid failed to take the element order of a vector into account. In order to further improve the encoding performance of the previous work [7], this paper proposes to introduce a dynamic element reordering operation to let all elements of a codeword rearranged in an ascending order by an offline sorting process before it goes to construct the mixed-pyramid for the codeword. After the element reordering, it is possible to make the intermediate levels in the mixed-pyramid of a codeword keep more energy and become more powerful for rejection tests. Experimental results confirmed that the encoding efficiency of the proposed method remarkably outperforms the previous work [7].

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U2 - 10.1109/ECCTD.2007.4529618

DO - 10.1109/ECCTD.2007.4529618

M3 - Conference contribution

AN - SCOPUS:49749095611

SN - 1424413427

SN - 9781424413423

T3 - European Conference on Circuit Theory and Design 2007, ECCTD 2007

SP - 404

EP - 407

BT - European Conference on Circuit Theory and Design 2007, ECCTD 2007

PB - IEEE Computer Society

T2 - European Conference on Circuit Theory and Design 2007, ECCTD 2007

Y2 - 26 August 2007 through 30 August 2007

ER -