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In this paper, we propose a novel data hiding method based on histogram framework which is essentially different from the conventional histogram-based data hiding methods. The conventional methods always use the peak point to embed the secret data and before the embedding all pixels between peak point and zero point must be shifted to zero point to provide an extra space for embedding. The distortion is mainly caused by this shifting operation. We propose using the border point of the histogram instead of peak point to embed the secret data so that the shifting can be completely avoided. Because there are no pixels between border point and extremum point (i.e. 0 or 255), there is no shifting before embedding. Then, to increase the embedding capacity, more border points are needed for embedding. Therefore, the localization is exploited to divide the cover image into non-overlapping blocks to generate more border points. Compared with other histogram-based data hiding methods, our proposed method provides higher image quality because the shifting is avoided, and the embedding capacity is also high due to the localization. Experimental results show that the PSNR of our proposed method is at least 5-10 dB higher than the related histogram-based data hiding methods under the same embedding capacity. [ABSTRACT FROM AUTHOR]

In recent years, many reversible data hiding techniques have been proposed to solve information security problem. In this paper, we propose a novel reversible data hiding method based on enhanced side-match vector quantization (ESMVQ). We embed as many secret bits into the images compressed by ESMVQ which uses the very small state codebook size of 4 to achieve a large hiding capacity and meanwhile ensure the compressed image quality by introducing a complementary state codebook. The experimental results demonstrate that the proposed method has a large embedding capacity and a good image quality. The experimental results also show that our proposed method outperforms the methods of Chang et al. (IEEE Trans on Circ and Syst for Vi Techno 16(10):1301-1308, ), Huang et al. (The Image Sci J 61(2):195-203, , Lee et al. (IEEE Trans on Inf Forensic and Secur 5(4):638-648, ) and Wang et al. (Inf Sci 246:69-82, ). [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 high-performance reversible data hiding method for vector quantization (VQ) indices is proposed. The codebook is firstly sorted using the unidirectional static distance-order technique to improve the correlation among the neighboring indices. The two-dimensional structure of image and the high correlation among the neighboring blocks are used to update the self-organized list L in the improved locally adaptive coding scheme (ILAS). Then a new embedding rule according to the complexity of the region at which the current block locates and the position of current block index in the list L is proposed to obtain a better embedding capacity. The experimental results demonstrate that our proposed method has a better performance in terms of compression rate, embedding capacity and embedding rate compared with the related data hiding methods. [ABSTRACT FROM AUTHOR]

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]

Reversible data hiding can completely recover the cover image without any distortion after the secret data is retrieved. In this paper, a new high-fidelity reversible data hiding scheme is proposed using the prediction-error histogram modification technique. A multi-predictor sorting and selecting mechanism is proposed to select an optimum predictor from a set of predictors. Then a smaller prediction-error is obtained to embed the secret data using the prediction-error histogram modification technique. Since the multi-predictor sorting and selecting mechanism can utilize the advantage of multi-predictor and information of current predicted pixel to obtain a more accurate prediction value, our proposed scheme can introduce less image distortion at the same embedding payload. Experimental results demonstrate that our proposed scheme outperforms the similar reversible data hiding schemes. [ABSTRACT FROM AUTHOR]