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In this paper, a novel reversible data hiding scheme for Two-stage VQ (Vector quantization) compressed images based on SOC (Search-order coding) scheme is proposed. Two-stage VQ improves VQ by obtaining better reconstructed image and generating indices with higher correlation. The difference image, as the input of Two-stage VQ, is produced by employing the first codeword in state codebook and the current image block. The main idea of SOC method is exploiting the correlation of indices to derive better compression performance. The combination of SOC and data hiding can achieve both high compression rate and high embedding capacity. Since Two-stage VQ can achieve indices with higher correlation, this advantage is applied to enhance the data hiding performance. Moreover, the cover image can be reconstructed by the receiver without using any side information. To show the superiority of our proposed scheme, several state-of-the-art schemes designed for compression domain are cited for comparison. [ABSTRACT FROM AUTHOR]

Side match vector quantisation (SMVQ) technique has been widely used in a lot of image compression and data hiding applications. It can effectively decrease the bit rate (BR) but the encoding visual quality of the image using SMVQ is generally poor because the correlation among neighbouring image blocks is still low. In this study, the authors propose a new enhanced SMVQ (ESMVQ) by introducing the concept of complementary state codebook (CSC) to improve the visual quality of SMVQ. Encoding input vectors by using CSC, ESMVQ can achieve almost the same encoding visual quality as using the conventional vector quantisation. As a result, the encoding visual quality of image can be significantly improved by exploiting the power of CSC. Experimental results show that the improvement of proposed ESMVQ method over SMVQ is up to 4.677 dB at a similar BR for image Lena when the main codebook size is 1024. [ABSTRACT FROM AUTHOR]

Abstract: Reversible data hiding is a method that not only embeds secret data but also reconstructs the original cover image without distortion after the confidential data are extracted. In this paper, we propose novel reversible data hiding scheme that can embed high capacity of secret bits and recover image after data extraction. Our proposed scheme depends on the locally adaptive coding scheme (LAC) as Chang&Nguyen’s scheme and SMVQ scheme. Experimental results show that the compression rate of our proposed scheme is 0.33bpp on average. To embed secret bits we propose the normal-hiding scheme and the over-hiding scheme which have an average embedding rate of 2.01bpi and 3.01bpi, more than that of Chang&Nguyen’s scheme (1.36bpi). The normal-hiding scheme and the over-hiding scheme also has high embedding efficiency of 0.28 and 0.36 on average, which are better than that of Chang&Kieu’s scheme (0.12), Chang&Nguyen’s scheme (0.18) and Chang&Nguyen’s scheme (0.16). [Copyright &y& Elsevier]

In this paper, a new reversible data hiding scheme for vector quantization (VQ) compressed images is proposed. The proposed scheme utilizes the modified locally adaptive coding scheme which is initially made up with the codebook indices to guarantee that all VQ indices can be coded using the self-organized list L. Then the side match vector quantization (SMVQ) approach is used to improve the performance of locally adaptive coding scheme and a lossless coding method is brought into encode the positions at which the VQ indices appear in the list L. Finally a double-layer embedding strategy, which embeds the secret message into two layers that are the block type descriptor and the encoded position value, is proposed to obtain a better embedding ability. The experimental results demonstrate that our proposed scheme has a better performance in terms of compression rate, embedding payload and embedding efficiency compared with the related schemes. [ABSTRACT FROM AUTHOR]