Abstract
Side match vector quantization (SMVQ) algorithm is an effective low bit rate image compression algorithm which is very useful for data hiding techniques. By replacing the main codebook used in conventional vector quantization (VQ) with a high-quality state codebook (SC) which consists of less codewords, SMVQ algorithm can achieve both much lower bit rate than VQ and acceptable visual quality. However, the generation of the SC is of high complexity that makes the applications of SMVQ limited. To overcome this bottleneck, inequality-based fast search algorithm is used in this paper. Experimental results show that by utilizing the mean feature and the variance feature of a vector, a majority of non-closest codewords in the main codebook can be rejected and the generation of SC can be efficiently speeded up. In addition, the SC generated by using our proposed algorithm is exactly the same as the SC generated by conventional SMVQ.
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