An SMVQ compressed data hiding scheme based on multiple linear regression prediction

被引:8
|
作者
Chi, Hengxiao [1 ]
Chang, Chin-Chen [1 ]
Liu, Yanjun [1 ]
机构
[1] Feng Chia Univ, Dept Informat Engn & Comp Sci, 100 Wenhwa Rd, Taichung 407, Taiwan
关键词
Data hiding; multiple linear regression; vector quantisation; side match vector quantisation; side-match distortion;
D O I
10.1080/09540091.2020.1852179
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a side matching vector quantisation (SMVQ) data hiding scheme for image using multiple linear regression prediction. For each pixel block, the proposed scheme combines the multiple linear regression algorithm and the SMVQ algorithm, so that it can more accurately match the codeword or directly obtain the predicted value closer to the real pixel. Our experimental results show that when the VQ codebook sizes are 128, 256, 512, and 1024, and the SCB size is 16, this scheme obtains a better compression rate and information embedding ability. It can be concluded from the experimental results that this scheme is superior to existing algorithms in terms of compression and embedding capacity.
引用
收藏
页码:495 / 514
页数:20
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