Title :
A fast search algorithm for vector quantization using L2-norm pyramid of codewords
Author :
Song, Byung Cheol ; Ra, Jong Beom
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
fDate :
1/1/2002 12:00:00 AM
Abstract :
Vector quantization for image compression requires expensive encoding time to find the closest codeword to the input vector. This paper presents a fast algorithm to speed up the closest codeword search process in vector quantization encoding. By using an appropriate topological structure of the codebook, we first derive a condition to eliminate unnecessary matching operations from the search procedure. Then, based on this elimination condition, a fast search algorithm is suggested. Simulation results show that with little preprocessing and memory cost, the proposed search algorithm significantly reduces the encoding complexity while maintaining the same encoding quality as that of the full search algorithm. It is also found that the proposed algorithm outperforms the existing search algorithms
Keywords :
image coding; search problems; vector quantisation; L2-norm pyramid; closest codeword search process; encoding complexity; fast search algorithm; image compression; topological structure; unnecessary matching operations; vector quantization; Computational complexity; Costs; Decoding; Distortion measurement; Encoding; Euclidean distance; Image coding; Rate-distortion; Speech coding; Vector quantization;
Journal_Title :
Image Processing, IEEE Transactions on