Reversible Data Hiding With Image Enhancement Using Histogram Shifting

Ying, Qichao; Qian, Zhenxing; Zhang, Xinpeng; Ye, Dengpan

doi:10.1109/access.2019.2909560

Cited by 38 publications

(27 citation statements)

References 35 publications

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“…Recently, Tang et al [18] applied HS to the design of RDH in encrypted image, and achieved data embedding by shifting block histogram of pixel differences in homomorphic encrypted domain. Ying et al [19] proposed a novel RDH algorithm based on contrast enhancement. This algorithm used the HS technique based on prediction error to achieve high embedding payload.…”

Section: Hs-based Rdh Algorithmsmentioning

confidence: 99%

“…The associate editor coordinating the review of this manuscript and approving it for publication was Jiju Poovvancheri . compression (LC) [7]- [11], difference expansion (DE) [12]- [14], histogram shifting (HS) [15]- [18], predictionerror expansion (PEE) [19]- [23] and integer transform (IT) [24]- [27]. Some typical algorithms of each category are briefly introduced as follows.…”

Section: Introductionmentioning

confidence: 99%

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Color Image Reversible Data Hiding With Double-Layer Embedding

et al. 2020

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Reversible data hiding (RDH) in color image is an important topic of data hiding. This paper presents an efficient RDH algorithm for color image via double-layer embedding. The key contribution is the proposed double-layer embedding technique based on histogram shifting (HS). This technique exploits image interpolation to generate prediction error matrices for HS in the first-layer embedding and uses local pixel similarity to calculate difference matrices for HS in the second-layer embedding. It inherits reversibility from HS and makes high embedding capacity due to the use of double layers in data embedding. In addition, inter-channel correlation is incorporated into the first-layer embedding and the second-layer embedding for generating histograms with high peaks, so as to improve embedding capacity. Experiments with open standard datasets are done to validate performance of the proposed RDH algorithm. Comparison results show that the proposed RDH algorithm outperforms some state-of-the-art RDH algorithms in terms of embedding capacity and visual quality. INDEX TERMS Reversible data hiding, histogram shifting, double-layer embedding, image interpolation, inter-channel correlation.

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Section: Hs-based Rdh Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Color Image Reversible Data Hiding With Double-Layer Embedding

et al. 2020

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“…In the past decade, many data hiding schemes have been proposed. Schemes [1]- [3] embedded the data in the spatial domain. Schemes [4]- [6] implemented the data hiding in the compressed domain.…”

Section: Introductionmentioning

confidence: 99%

Fidelity Preserved Data Hiding in Encrypted Images Based on Homomorphism and Matrix Embedding

2020

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This paper proposes a data hiding scheme for high quality stego-images in the encrypted images based on a homomorphic encryption algorithm and matrix embedding method. To achieve the message embedding in the encryption domain, we first present an image encryption algorithm satisfying additive homomorphism based on the stream cipher. Then, we offer a matrix embedding method using Golay code, which has good embedding efficiency. In the proposed scheme, we pre-code the least significant bit (LSB) vectors of the cover image into the codewords before image encryption, so that we can implement the matrix embedding in the encrypted image. The experimental results show that the proposed scheme has excellent security performance. We can get a high quality stego-image after the image decryption and recover the cover image into a fidelity image while providing considerable payload. INDEX TERMS Fidelity preserved, homomorphism, matrix embedding, Golay code, data hiding, encrypted image.

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“…Information hiding is to embed secret data to the image, video or other public carriers, and makes them less susceptible and difficult for adversaries to detect. This paper studies and proposes a novel method of information hiding, which has practical application value for copyright and intellectual property protection [4], labeling digital images [5], company…”

Section: Introductionmentioning

confidence: 99%

Modulus Calculations on Prime Number Algorithm for Information Hiding With High Comprehensive Performance

Zhang

Wang

et al. 2020

IEEE Access

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Information hiding is an important technique for information security, which is wildly studied by researchers. Recently embedding methods are proposed in spatial, frequency and other domains. After investigating previous literatures, we find that there is still room for embedding performance improvement. Inspired by some literatures, we propose a new method (Modulus Calculations on Prime Number Algorithm, MOPNA) for embedding secret data into cover-images. The main idea of MOPNA is hiding confidential data in paired cover-pixels with modulus calculation based on weight parameters consisting of prime numbers. MOPNA improves the embedding capacity while maintaining good stego-image quality. The correctness of MOPNA method is proved by a combination of mathematical and programming proof. The experimental results prove that the proposed method has high embedding capacity and achieves better comprehensive performance than existing methods.

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Reversible Data Hiding With Image Enhancement Using Histogram Shifting

Cited by 38 publications

References 35 publications

Color Image Reversible Data Hiding With Double-Layer Embedding

Color Image Reversible Data Hiding With Double-Layer Embedding

Fidelity Preserved Data Hiding in Encrypted Images Based on Homomorphism and Matrix Embedding

Modulus Calculations on Prime Number Algorithm for Information Hiding With High Comprehensive Performance

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