Dual-image reversible data hiding based on pixel value parity and multiple embedding strategy

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Signal Processing Pub Date : 2024-11-04 DOI:10.1016/j.sigpro.2024.109764
Hua Zhang , Zhenghong Peng , Fanli Meng
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Abstract

Dual-image reversible data hiding (DI-RDH) has attracted a lot of attention for its excellent embedding capability. However, the stego image after data embedding is degraded, which limits its practical application. This paper proposes an innovative DI-RDH method based on pixel value parity (PVP), which prevents influences from the image texture features and ensures that the pixel value deviation between the temporary stego image and the original image is −1, 0, or 1, as it can partially offset the difference introduced when generating the cover image. Such characteristics enable us to establish a multiple embedding strategy (MES), which applies the difference image to embed the secret message, decreasing the number of invalid shifting pixels in the difference histogram to enhance embedding capacity and image quality. The average maximum embedding rate of our method combining PVP and two phases of MES is determined to be 1.37 bpp, corresponding to the theoretical results. The average peak signal-to-noise ratio of our method on the UCID database is increased by at least 2.19 dB for a given ER of 0.5 bpp compared with several state-of-the-art methods.
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基于像素值奇偶校验和多重嵌入策略的双图像可逆数据隐藏
双图像可逆数据隐藏(DI-RDH)因其出色的嵌入能力而备受关注。然而,数据嵌入后的伪图像质量下降,限制了其实际应用。本文提出了一种创新的基于像素值奇偶校验(PVP)的 DI-RDH 方法,它能防止图像纹理特征的影响,并确保临时偷窃图像与原始图像之间的像素值偏差为-1、0 或 1,因为它能部分抵消生成覆盖图像时引入的差异。这种特性使我们能够建立一种多重嵌入策略(MES),利用差分图像嵌入秘密信息,减少差分直方图中无效位移像素的数量,从而提高嵌入能力和图像质量。我们的方法结合了 PVP 和两个阶段的 MES,其平均最大嵌入率为 1.37 bpp,与理论结果相符。与几种最先进的方法相比,我们的方法在 UCID 数据库中的平均峰值信噪比在给定 ER 为 0.5 bpp 的情况下至少提高了 2.19 dB。
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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