Zhibin Pan

Reversible data hiding based on local histogram shifting with multilayer embedding

We use the two neighboring points of the peak point to embed the secret data.We improve the histogram of embedded cover image to ensure security of secret data.The multilayer embedding of pyramid structure is adopted to increase the capacity.Our proposed method has a higher embedding capacity with lower distortion. 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.

Low bit-rate information hiding method based on search-order-coding technique

Information hiding method with low bit rate is important in secure communications. To reduce bit rate we propose a new embedding method in this paper based on SOC (search-order coding) compression technique. Compared to Chang et al.s scheme in 2004, our scheme completely avoids the transform from SOC coding to OIV (original index values) coding to significantly reduce bit rate. In order to further reduce bit rate, Chang et al. proposed a reversible data hiding scheme using hybrid encoding strategies by introducing the side-match vector quantization (SMVQ) in 2013. But it needed additional 1 bit indicator to distinguish the two statuses to determine OIV is belonged to G1 or G2. This overhead gave a large burden to compression rate and could not reduce the bit rate significantly. In contrast, our scheme completely avoids this indicator. The experimental results show that the proposed method can efficiently reduce the bit rate and have the same embedding capacity compared with Chang et al.s scheme in 2004 and Chang et al.s scheme in 2013. Moreover, our proposed scheme can also achieve a better performance in both the embedding capacity and bit rate than other related VQ-based information hiding schemes.

A novel high-performance reversible data hiding scheme using SMVQ and improved locally adaptive coding method

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&Nguyens 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&Nguyens 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&Kieus scheme (0.12), Chang&Nguyens scheme (0.18) and Chang&Nguyens scheme (0.16).

Reversible data hiding scheme for VQ indices based on modified locally adaptive coding and double-layer embedding strategy

We propose a coding method using modified locally adaptive coding.Double-layer embedding strategy is proposed to obtain a better embedding ability.Experiments show our scheme has a better performance compared with other schemes. 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.

New reversible full-embeddable information hiding method for vector quantisation indices based on locally adaptive complete coding list

Steganography based on vector quantisation (VQ)-compressed indices is widely used in information hiding. In this study, the authors propose a new reversible information hiding method for VQ indices using an on-line generated locally adaptive complete coding list. The complete coding list guarantees that all VQ indices can embed one or two secret bits which efficiently increase the embedding capacity. Additionally, they propose a mixed coding method with an index position threshold by exploring the biased-distribution of locally complete coding indices in order to reduce the bit rate. Experimental results demonstrated that the authors proposed method has a better performance in embedding capacity, bit rate and the embedding-efficiency compared with the four information hiding methods.

Enhanced side match vector quantisation based on constructing complementary state codebook

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.

Novel Reversible Data Hiding Scheme for Two-stage VQ Compressed Images Based on Search-order Coding

Abstract 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.

A novel reversible data hiding scheme by introducing current state codebook and prediction strategy for joint neighboring coding

Reversible data hiding (RDH) in compression domain is an important research issue in the security of digital multimedia. Obtaining a high embedding rate and a low compression rate are the main goals of compression domain RDH. This paper proposes a novel RDH scheme to improve joint neighboring coding (JNC) scheme. In embedding process, the first index SC1st in current state codebook (SC) and median edge detector (MED) prediction Pmed are exploited. These two parameters are employed to replace the right-up and left-up neighboring SMVQ indices, which have lower correlation with the current index. As a result, a more concentrated distribution of difference “d” is obtained. Difference “d” is computed by the difference between the current SMVQ index and its left, upper neighboring indices, Pmed and SC1st after embedding secret bits. The experimental results show that our work achieves the average compression rate of 0.45/0.51/0.57 bpp and the average embedding efficiency of 0.28/0.36/0.43 after embedding 2/3/4 bits secret data into each SMVQ index. As demonstrated in the comparative results, it can be observed that the proposed scheme outperforms the other previous works.

A novel reversible data hiding scheme using SMVQ prediction index and multi-layer embedding

In this paper, a novel reversible data hiding scheme which utilizes SMVQ prediction indices to embed secret data is proposed. As a result, it improves Yang’s work, which takes advantage of counts of indices in data embedding. Our approach enhances the prediction of SMVQ, resulting in a more concentrated distribution of indices. Based on the distribution of SMVQ-p indices, in the embedding process, three clusters (CL0, CL1 and CL2) are defined. Indices in CL0 are employed to embed secret data and can support a high embedding capacity. Indices in cluster CL1 are employed for supporting a lower bit rate. Indices in cluster CL2 are utilized for lossless reconstruction. Experimental results indicate that lower bit rate and higher embedding efficiency are obtained after encoding and embedding processes by our approach. Furthermore, experimental results demonstrate that the proposed method outperforms other state-of-the-art reversible data hiding schemes as well.

Large capacity and high quality reversible data hiding method based on enhanced side match vector quantization

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, 2006), Huang et al. (The Image Sci J 61(2):195–203, 2013), Lee et al. (IEEE Trans on Inf Forensic and Secur 5(4):638–648, 2010) and Wang et al. (Inf Sci 246:69–82, 2013).