Xiaoxiao Ma

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.

High-fidelity reversible data hiding scheme based on multi-predictor sorting and selecting mechanism

We propose a reversible data hiding scheme using histogram modification technique.A new mechanism is proposed to select an optimum predictor from a set of predictors.A smaller prediction-error is obtained using our proposed mechanism.The prediction-error histogram is modified to embed the secret data.Experiments show our scheme outperforms the similar schemes. 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.

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.

New high-performance reversible data hiding method for VQ indices based on improved locally adaptive coding scheme

We propose a new data hiding method using improved locally adaptive coding (ILAS).ILAS uses the two-dimensional structure of image and correlation of adjacent indices.Our proposed ILAS can significantly improve the performance of LAS.Experiments show our method has a better performance compared with other methods. 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.

A new lossless data hiding method based on joint neighboring coding

The codebook is sorted according to the side-match distortion.The residual value is calculated by exclusive-OR operation.There are different coding rules according to the characteristics of parameter m. In this paper, we present a new reversible data hiding method based on joint neighboring coding. The proposed method uses the side-match distortion (SMD) function to sort the codebook so as to make an index value become very close to its neighboring index values, then the residual value between the index and its neighboring index is obtained by bitwise exclusive-OR operation and the secret bits are embedded into the residual value according to our embedding rules based on joint neighboring coding. The experimental results show our proposed method outperforms the related existing data hiding methods in embedding performance.

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.

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).