Search

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]

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, we present a new reversible data hiding method based on histogram shifting using localization. Our proposed method selects peak point as the reference point, then uses the two neighboring points of the peak point to achieve secret data embedding based on histogram shifting and the peak point keeps unchanged. In the extraction end, we no longer need the key information about the peak point, we can directly find the peak point from the histogram to extract the secret data. We also exploit the localization to make the histogram of embedded cover image become almost the same as the histogram of the original cover image. The embedding capacity is also increased rapidly by the localization with multilayer embedding. Experimental results show that our proposed method is effective and superior. [ABSTRACT FROM AUTHOR]

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]