Reversible data hiding using multi-pass pixel value ordering and prediction-error expansion

He, Weiji; Zhou, Ke; Cai, Jie; Wang, Long; Xiong, Ge

doi:10.1016/j.jvcir.2017.10.001

Cited by 56 publications

(33 citation statements)

References 35 publications

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“…These results demonstrates that the proposed scheme is fragile against various manipulations. approaches, found in literature, can perform equally but most of them lack our simplicity [20,25,28]. Visual image quality is tested after hiding various payload magnitudes (0.05bpp, 0.1bpp, 0.15bpp, 0.2bpp, 0.25bpp).…”

Section: Comparison With Existing Approachesmentioning

confidence: 99%

“…Therefore, fully reversible watermarking techniques, which can completely recover both the original unmodified image and the embedded watermark, are developed. Reversible watermarking approaches can be categorized into four groups: compression based [7,10], histogram modification based [16,21,33], quantization based [22,23] and Difference Expansion (DE) based [20,28]. Reversible watermarking based on the DE technique are recommended by many recent studies, and typically exceed alternate reversible methods in terms of higher payload capacity and lower complexity [20,28,41].…”

Section: Introductionmentioning

confidence: 99%

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ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Qasim

Aspin

Meziane

et al. 2018

Multimed Tools Appl

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Reversible and imperceptible watermarking is recognized as a robust approach to confirm the integrity and authenticity of medical images and to verify that alterations can be detected and tracked back. In this paper, a novel blind reversible watermarking approach is presented to detect intentional and unintentional changes within brain Magnetic Resonance (MR) images. The scheme segments images into two parts; the Region of Interest (ROI) and the Region of Non Interest (RONI). Watermark data is encoded into the ROI using reversible watermarking based on the Difference Expansion (DE) technique. Experimental results show that the proposed method, whilst fully reversible, can also realize a watermarked image with low degradation for reasonable and controllable embedding capacity. This is fulfilled by concealing the data into 'smooth' regions inside the ROI and through the elimination of the large location map required for extracting the watermark and retrieving the original image. Our scheme delivers highly imperceptible watermarked images, at 92.18-99.94 dB Peak Signal to Noise Ratio (PSNR) evaluated through implementing a clinical trial based on relative Visual Grading Analysis (relative VGA). This trial defines the level of modification that can be applied to medical images without perceptual distortion. This compares favorably to outcomes reported under current state-of-art techniques. Integrity and authenticity of medical images are also ensured through detecting subsequent changes enacted on the watermarked images. This enhanced security measure, therefore, enables the detection of image manipulations, by an imperceptible approach, that may establish increased trust in the digital medical workflow.

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Section: Comparison With Existing Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Qasim

Aspin

Meziane

et al. 2018

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…and C(i,j) =C(i,j). Otherwise, L 2 (i,j)=0 and s is embedded according to (12). Moreover, secret bits are not embedded into those pixels marked by L 1 and L 2 .…”

Section: Data Embedding With Additive Homomorphismmentioning

confidence: 99%

“…DE based algorithms usually shift the difference of neighboring pixels for creating a vacant least significant bit (LSB) and append one secret bit to the vacated LSB [5,6]. The HS based algorithms firstly shift the bins of histogram of gray values [7] or the predicted errors [8][9][10][11][12] for generating vacated space and then embed secret data into the vacated space. This kind of algorithms can provide a good trade-off between embedding capacity and visual quality.…”

Section: Introductionmentioning

confidence: 99%

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Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

Zhang

Tang

et al. 2018

Security and Communication Networks

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Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

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Generalized PVO‐based dynamic block reversible data hiding for secure transmission using firefly algorithm

Abbasi

Qureshi

Hassan

et al. 2019

Trans Emerging Tel Tech

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Reversible data hiding using multi-pass pixel value ordering and prediction-error expansion

Cited by 56 publications

References 35 publications

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

Generalized PVO‐based dynamic block reversible data hiding for secure transmission using firefly algorithm

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