Reversible data hiding

doi:10.1007/978-3-540-31805-7_1

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Reversible data hiding

Book Chapter•DOI•

Reversible data hiding

Zhicheng Ni¹, Yun-Qing Shi¹, Nirwan Ansari¹, Wei Su¹•Institutions (1)

New Jersey Institute of Technology¹

25 May 2003-Vol. 2, pp 1-12

TL;DR: A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms.

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Abstract: This paper presents a novel reversible data hiding algorithm, which can recover the original image without distortion from the marked image after the hidden data have been extracted. This algorithm utilizes the zero or the minimum point of the histogram and slightly modifies the pixel values to embed data. It can embed more data as compared to most of the existing reversible data hiding algorithms. A theoretical proof and numerous experiments show that the PSNR of the marked image generated by this method is always above 48 dB, which is much higher than other reversible data hiding algorithms. The algorithm has been applied to a wide range of different images successfully. Some experimental results are presented to demonstrate the validity of the algorithm.

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Journal Article•DOI•

Expansion Embedding Techniques for Reversible Watermarking

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D.M. Thodi¹, Jeffrey J. Rodriguez¹•Institutions (1)

University of Arizona¹

01 Mar 2007-IEEE Transactions on Image Processing

TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.

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Abstract: Reversible watermarking enables the embedding of useful information in a host signal without any loss of host information. Tian's difference-expansion technique is a high-capacity, reversible method for data embedding. However, the method suffers from undesirable distortion at low embedding capacities and lack of capacity control due to the need for embedding a location map. We propose a histogram shifting technique as an alternative to embedding the location map. The proposed technique improves the distortion performance at low embedding capacities and mitigates the capacity control problem. We also propose a reversible data-embedding technique called prediction-error expansion. This new technique better exploits the correlation inherent in the neighborhood of a pixel than the difference-expansion scheme. Prediction-error expansion and histogram shifting combine to form an effective method for data embedding. The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion. There is also a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities

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1,229 citations

Journal Article•DOI•

Reversible Data Hiding Based on Histogram Modification of Pixel Differences

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Wei-Liang Tai¹, Chia-Ming Yeh², Chin-Chen Chang²•Institutions (2)

National Chung Cheng University¹, Feng Chia University²

01 Jun 2009-IEEE Transactions on Circuits and Systems for Video Technology

TL;DR: A binary tree structure is exploited to solve the problem of communicating pairs of peak points and distribution of pixel differences is used to achieve large hiding capacity while keeping the distortion low.

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Abstract: In this letter, we present a reversible data hiding scheme based on histogram modification. We exploit a binary tree structure to solve the problem of communicating pairs of peak points. Distribution of pixel differences is used to achieve large hiding capacity while keeping the distortion low. We also adopt a histogram shifting technique to prevent overflow and underflow. Performance comparisons with other existing schemes are provided to demonstrate the superiority of the proposed scheme.

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550 citations

Cites background from "Reversible data hiding"

...in [18], in which the message is embedded into the histogram bin....
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...6 compares the pure payload of the “Lena” image in b/pixel versus image quality in PSNR delivered by the proposed scheme and other existing reversible schemes [7]–[9], [18]–[20]....
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...’s scheme [18] has low hiding capacity compared to those of...
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...Note that the proposed scheme and schemes [7], [18]–[20] are proposed in the spatial domain, whereas schemes [8], [9] are presented in the transform domain....
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...Schemes [18]–[20] are presented based on histogram modification; nevertheless, their algorithms did not provide a solution to the problem of communicating multiple pairs of peak and minimum points....
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Journal Article•DOI•

DE-Based Reversible Data Hiding With Improved Overflow Location Map

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Yongjian Hu¹, Heung-Kyu Lee¹, Jianwei Li²•Institutions (2)

KAIST¹, South China University of Technology²

01 Feb 2009-IEEE Transactions on Circuits and Systems for Video Technology

TL;DR: A new embedding scheme is designed that helps to construct an efficient payload-dependent overflow location map that has good compressibility and accurate capacity control capability and reduces unnecessary alteration to the image.

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Abstract: For difference-expansion (DE)-based reversible data hiding, the embedded bit-stream mainly consists of two parts: one part that conveys the secret message and the other part that contains embedding information, including the 2-D binary (overflow) location map and the header file. The first part is the payload while the second part is the auxiliary information package for blind detection. To increase embedding capacity, we have to make the size of the second part as small as possible. Tian's classical DE method has a large auxiliary information package. Thodi mitigated the problem by using a payload-independent overflow location map. However, the compressibility of the overflow location map is still undesirable in some image types. In this paper, we focus on improving the overflow location map. We design a new embedding scheme that helps us construct an efficient payload-dependent overflow location map. Such an overflow location map has good compressibility. Our accurate capacity control capability also reduces unnecessary alteration to the image. Under the same image quality, the proposed algorithm often has larger embedding capacity. It performs well in different types of images, including those where other algorithms often have difficulty in acquiring good embedding capacity and high image quality.

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479 citations

Cites background from "Reversible data hiding"

...[4] proposed a scheme of using peak/zero points in the histogram of spatial domain images....
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Journal Article•DOI•

General Framework to Histogram-Shifting-Based Reversible Data Hiding

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Xiaolong Li¹, Bin Li², Bin Yang¹, Tieyong Zeng³•Institutions (3)

Peking University¹, Shenzhen University², Hong Kong Baptist University³

01 Jun 2013-IEEE Transactions on Image Processing

TL;DR: This paper revisits the HS technique and presents a general framework to construct HS-based RDH, and shows that several RDH algorithms reported in the literature are special cases of this general construction.

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Abstract: Histogram shifting (HS) is a useful technique of reversible data hiding (RDH). With HS-based RDH, high capacity and low distortion can be achieved efficiently. In this paper, we revisit the HS technique and present a general framework to construct HS-based RDH. By the proposed framework, one can get a RDH algorithm by simply designing the so-called shifting and embedding functions. Moreover, by taking specific shifting and embedding functions, we show that several RDH algorithms reported in the literature are special cases of this general construction. In addition, two novel and efficient RDH algorithms are also introduced to further demonstrate the universality and applicability of our framework. It is expected that more efficient RDH algorithms can be devised according to the proposed framework by carefully designing the shifting and embedding functions.

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352 citations

Cites background or methods from "Reversible data hiding"

...Besides aforementioned works [11]–[13], [22], many HS-based RDH algorithms have also been proposed so far [23]–[31]....
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...’s HS-based algorithm [11] is another important work of RDH, in which the peak of image histogram is utilized to embed data....
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...2246179 difference expansion (DE) [8]–[10], histogram shifting (HS) [11]–[13], and integer transform [14]–[17], etc....
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Journal Article•DOI•

Multilevel reversible data hiding based on histogram modification of difference images

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Chia-Chen Lin¹, Wei-Liang Tai², Chin-Chen Chang²•Institutions (2)

Providence College¹, National Chung Cheng University²

01 Dec 2008-Pattern Recognition

TL;DR: This paper proposes a multilevel reversible data hiding scheme based on the difference image histogram modification that uses the peak point to hide messages through a joint imperceptibility and hiding capacity evaluation.

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324 citations

Cites background or methods from "Reversible data hiding"

...[17] used the zero point and peak point of an image histogram to hide message and achieved reversibility....
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...'s scheme [17] we explore the peak point of the histogram in pixel differences in an image, then slightly modify the pixel values to hide the embedded message....
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...'s scheme [17], in which all peak points are concatenated as a secret key and are transmitted to the receiver side for extraction of the embeddedmessage and restoration of the original image....
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...'s scheme [17] has low hiding capacity compared to the others....
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...'s scheme [17], DE of triplets [13], and Chang et al....
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References

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Journal Article•DOI•

Secure spread spectrum watermarking for multimedia

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Ingemar J. Cox¹, J. Kilian¹, F.T. Leighton¹, Talal G. Shamoon¹•Institutions (1)

Princeton University¹

01 Dec 1997-IEEE Transactions on Image Processing

TL;DR: It is argued that insertion of a watermark under this regime makes the watermark robust to signal processing operations and common geometric transformations provided that the original image is available and that it can be successfully registered against the transformed watermarked image.

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Abstract: This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.

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6,194 citations

"Reversible data hiding" refers methods in this paper

...With the most popularly utilized spread-spectrum watermarking techniques, either in DCT domain [1] or block 8x8 DCT domain [2], roundoff error and/or truncation error may take place during data embedding....
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Journal Article•DOI•

Techniques for data hiding

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Walter Bender¹, Daniel Gruhl¹, Norishige Morimoto², Aiguo Lu¹•Institutions (2)

Massachusetts Institute of Technology¹, IBM²

01 Sep 1996-Ibm Systems Journal

TL;DR: This work explores both traditional and novel techniques for addressing the data-hiding process and evaluates these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.

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Abstract: Data hiding, a form of steganography, embeds data into digital media for the purpose of identification, annotation, and copyright. Several constraints affect this process: the quantity of data to be hidden, the need for invariance of these data under conditions where a "host" signal is subject to distortions, e.g., lossy compression, and the degree to which the data must be immune to interception, modification, or removal by a third party. We explore both traditional and novel techniques for addressing the data-hiding process and evaluate these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.

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3,037 citations

Additional excerpts

...[20] proposed a reversible data hiding algorithm based on patchwork theory [21], which has certain robustness against JPEG lossy compression....
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Journal Article•DOI•

Reversible data embedding using a difference expansion

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Jun Tian

01 Aug 2003-IEEE Transactions on Circuits and Systems for Video Technology

TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.

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Abstract: Reversible data embedding has drawn lots of interest recently Being reversible, the original digital content can be completely restored We present a novel reversible data-embedding method for digital images We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low

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2,739 citations

"Reversible data hiding" refers background or methods or result in this paper

...Tian presented a promising high capacity reversible data embedding algorithm in [15]....
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...Later, a difference expansion scheme was developed by Tian [15], which has greatly advanced the performance of reversible data hiding in terms of data embedding capacity versus PSNR of marked images with respect to original images....
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...[16,17], which have demonstrated superior performance over that reported in [15]....
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...It has been reported in [15] that the embedding capacity achieved by the difference expansion method is much higher than that achieved by [10]....
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Book Chapter•DOI•

Factoring wavelet transforms into lifting steps

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Ingrid Daubechies¹, Wim Sweldens²•Institutions (2)

Princeton University¹, Alcatel-Lucent²

01 May 1998-Journal of Fourier Analysis and Applications

TL;DR: In this paper, a self-contained derivation from basic principles such as the Euclidean algorithm, with a focus on applying it to wavelet filtering, is presented, which asymptotically reduces the computational complexity of the transform by a factor two.

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Abstract: This article is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures. This decomposition corresponds to a factorization of the polyphase matrix of the wavelet or subband filters into elementary matrices. That such a factorization is possible is well-known to algebraists (and expressed by the formulaSL(n;R[z, z−1])=E(n;R[z, z−1])); it is also used in linear systems theory in the electrical engineering community. We present here a self-contained derivation, building the decomposition from basic principles such as the Euclidean algorithm, with a focus on applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the biorthogonal, i.e., non-unitary case. Like the lattice factorization, the decomposition presented here asymptotically reduces the computational complexity of the transform by a factor two. It has other applications, such as the possibility of defining a wavelet-like transform that maps integers to integers.

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2,357 citations

"Reversible data hiding" refers methods in this paper

...To increase the payload dramatically, a new lossless data hiding technique [17] based on integer wavelet transform (IWT) [18], [19] (a second generation wavelet transform, which has avoided round-off errors) was developed recently....
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Journal Article•DOI•

Quantization index modulation: a class of provably good methods for digital watermarking and information embedding

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Brian Chen¹, Gregory W. Wornell¹•Institutions (1)

Massachusetts Institute of Technology¹

25 Jun 2000

TL;DR: It is shown that QIM is "provably good" against arbitrary bounded and fully informed attacks, and achieves provably better rate distortion-robustness tradeoffs than currently popular spread-spectrum and low-bit(s) modulation methods.

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Abstract: We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing the information-embedding rate, minimizing the distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We introduce new classes of embedding methods, termed quantization index modulation (QIM) and distortion-compensated QIM (DC-QIM), and develop convenient realizations in the form of what we refer to as dither modulation. Using deterministic models to evaluate digital watermarking methods, we show that QIM is "provably good" against arbitrary bounded and fully informed attacks, which arise in several copyright applications, and in particular it achieves provably better rate distortion-robustness tradeoffs than currently popular spread-spectrum and low-bit(s) modulation methods. Furthermore, we show that for some important classes of probabilistic models, DC-QIM is optimal (capacity-achieving) and regular QIM is near-optimal. These include both additive white Gaussian noise (AWGN) channels, which may be good models for hybrid transmission applications such as digital audio broadcasting, and mean-square-error-constrained attack channels that model private-key watermarking applications.

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2,218 citations

"Reversible data hiding" refers methods in this paper

...With the third group of frequently used watermarking techniques, called quantization index modulation (QIM) [ 3 ], quantization error renders lossy data hiding....
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