A fast search algorithm for vector quantization using L2-norm pyramid of codewords
IEEE Transactions on Image Processing
An efficient encoding algorithm for vector quantization based on subvector technique
IEEE Transactions on Image Processing
Fast-searching algorithm for vector quantization using projection and triangular inequality
IEEE Transactions on Image Processing
Fast VQ encoding by an efficient kick-out condition
IEEE Transactions on Circuits and Systems for Video Technology
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A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.