Reversible Data Hiding in Color Image With Grayscale Invariance

Hou, Dongdong; Zhang, Weiming; Chen, Kejiang; Lin, Sian-Jheng; Yu, Nenghai

doi:10.1109/tcsvt.2018.2803303

Cited by 61 publications

(46 citation statements)

References 38 publications

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“…This RDH algorithm outperforms conventional PEE-based algorithm. In another study, Hou et al [35] introduced a novel color image RDH algorithm with grayscale invariance. This algorithm can embed data into color image without changing gray version of the color host image and thus the further use of the marked image is not affected.…”

Section: E It-based Rdh Algorithmsmentioning

confidence: 99%

“…To demonstrate advantages, our proposed RDH algorithm is compared with some state-of-the-art RDH algorithms. The selected RDH algorithms are Ou et al's algorithm [31], Yao et al's algorithm [32], and Hou et al's algorithm [35], which are all designed for color images and recently published in famous journals. Figure 9 demonstrates performance comparison with respect to PSNR and embedding capacity based on eight standard benchmark color images sized 512 × 512.…”

Section: Performance Comparisonsmentioning

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: E It-based Rdh Algorithmsmentioning

confidence: 99%

Section: Performance Comparisonsmentioning

confidence: 99%

Color Image Reversible Data Hiding With Double-Layer Embedding

et al. 2020

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“…Different from audio, an image is a two-dimensional signal in the spatial domain, so the focus of the embedding process is to find stable image elements in the spatial domain. Hou et al [10] used the gray-scale invariance feature to embed a watermark by changing the red, green and blue channels. Based on the immutability of the gray version, the watermark extraction is completed by predicting and restoring the red and green channel values.…”

Section: A Prior Related Approachesmentioning

confidence: 99%

Dual-Domain Audio Watermarking Algorithm Based on Flexible Segmentation and Adaptive Embedding

et al. 2019

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This paper proposes a novel dual-domain audio watermarking approach based on flexible segmentation and adaptive embedding aimed to improve robustness and imperceptibility. Compared with conventional watermarking strategies, the proposed approach has two advantages. First, a novel audio beat detection approach is designed to flexibly segment the audio, which provides stronger robustness to synchronization attacks. The audio is decomposed by the discrete wavelet packet transform. Then, the covariance relationships of the decomposition coefficients at different time instants are calculated to determine the locations of the beats and to establish a flexible segmentation model. Second, a dual-domain embedding approach is proposed to realize better robustness to compression attacks while maintaining imperceptibility. In each segment, the psychoacoustic model is used to calculate the audio masking threshold, which divides the signals into the masking signal domain and masked signal domain. The signals in the masking signal domain are robust to compression attacks, and the signals in the masked signal domain have better imperceptibility. To combine these advantages, we embed the watermark into the two domains simultaneously by using the distortion-compensated dither modulation quantization approach. To reduce the impact of the watermark on the original audio, the frequency band with the lowest mask-to-noise ratio is selected as the embedding position for each domain. Moreover, the adaptive quantization steps are calculated to control the embedding strength according to the masking effect. The adaptive embedding will improve the robustness to compression attacks without significantly affecting the original audio quality. The effectiveness of our approach is verified through simulation experiments. INDEX TERMS Audio beats, dual-domain, DWPT, DC-DM, psychoacoustic model.

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“…That is to say, the cover must be fully recovered after the additional data is extracted. This technology is named reversible data hiding (RDH) [1]- [9], it can be employed in many fields, such as military, medicine, forensics and so on.…”

Section: Introductionmentioning

confidence: 99%

Reversible Data Hiding in JPEG Images With Multi-Objective Optimization

Yin

Jiyuan

LuoBin

2020

IEEE Trans. Circuits Syst. Video Technol.

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Among various methods of reversible data hiding (RDH) in JPEG images, the consideration in designing is only the image quality, but the image quality and the file size expansion are equally important in JPEG images. Based on this situation, we propose a RDH scheme in JPEG images considering both the image quality and the file size expansion while designing the algorithm. The multi-objective optimization strategy is utilized to realize the balance of the two objectives. Specifically, the cover is divided into several non-overlapping signals firstly, and after that, the embedding costs of signals are calculated using the knowledge of the JPEG compression. Next, the optimized combination of signals for embedding data is gained by the multi-objective optimization. Experimental results show the better performance of our proposed RDH compared with state-of-the-art RDH in JPEG images.

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Reversible Data Hiding in Color Image With Grayscale Invariance

Cited by 61 publications

References 38 publications

Color Image Reversible Data Hiding With Double-Layer Embedding

Color Image Reversible Data Hiding With Double-Layer Embedding

Dual-Domain Audio Watermarking Algorithm Based on Flexible Segmentation and Adaptive Embedding

Reversible Data Hiding in JPEG Images With Multi-Objective Optimization

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