Multi-level encrypted reversible data hiding using histogram shifting for configurable embedding rate

2015 ◽  
Author(s):  
Arun K Mohan ◽  
Saranya M R ◽  
K Anusudha
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Multi Level ◽  
Embedding Rate

scholarly journals Reversible Data Hiding Based on Adaptive Block Selection Strategy

2020 ◽  
Vol 12 (1) ◽  
pp. 157-168
Author(s):  
Dan Huang ◽  
Fangjun Huang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Visual Quality ◽  
Original Method ◽  
Experimental Results ◽  
Selection Strategy ◽  
Original Image ◽  
Histogram Shifting ◽  
Carrier Image ◽  
Embedding Rate

Recently, a reversible data hiding (RDH) method was proposed based on local histogram shifting. This method selects the peak bin of the local histogram as a reference and expands the two neighboring bins of the peak bin to carry the message bits. Since the peak bin keeps unchanged during the embedding process, the neighboring bins can be easily identified at the receiver end, and the original image can be restored completely while extracting the embedded data. In this article, as an extension of the algorithm, the authors propose an RDH scheme based on adaptive block selection strategy. Via a new block selection strategy, those blocks of the carrier image may carry more message bits whereas introducing less distortion will take precedence over data hiding. Experimental results demonstrate that higher visual quality can be obtained compared with the original method, especially when the embedding rate is low.

scholarly journals Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Computers ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 86
Author(s):  
Jijun Wang ◽  
Soo Fun Tan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Order ◽  
Coding Method ◽  
Military Applications ◽  
Social Cloud ◽  
Carrier Image ◽  
Security Surveillance ◽  
Embedding Rate

Separable Reversible Data Hiding in Encryption Image (RDH-EI) has become widely used in clinical and military applications, social cloud and security surveillance in recent years, contributing significantly to preserving the privacy of digital images. Aiming to address the shortcomings of recent works that directed to achieve high embedding rate by compensating image quality, security, reversible and separable properties, we propose a two-tuples coding method by considering the intrinsic adjacent pixels characteristics of the carrier image, which have a high redundancy between high-order bits. Subsequently, we construct RDH-EI scheme by using high-order bits compression, low-order bits combination, vacancy filling, data embedding and pixel diffusion. Unlike the conventional RDH-EI practices, which have suffered from the deterioration of the original image while embedding additional data, the content owner in our scheme generates the embeddable space in advance, thus lessening the risk of image destruction on the data hider side. The experimental results indicate the effectiveness of our scheme. A ratio of 28.91% effectively compressed the carrier images, and the embedding rate increased to 1.753 bpp with a higher image quality, measured in the PSNR of 45.76 dB.

scholarly journals Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 917
Author(s):  
Limengnan Zhou ◽  
Hongyu Han ◽  
Hanzhou Wu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Hot Spot ◽  
Data Embedding ◽  
Histogram Shifting ◽  
Secret Data ◽  
Content Selection ◽  
Wide Range ◽  
Map Generation ◽  
Content Adaptive

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

scholarly journals Taylor expansion based stereo image reversible data hiding

2020 ◽  
Author(s):  
Xinyang Ying ◽  
Guobing Zhou
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Taylor Expansion ◽  
Stereo Image ◽  
Embedding Capacity ◽  
Stereo Images ◽  
Secret Data ◽  
Stego Image ◽  
Multi Level

Abstract The reversible data hiding allows original image to be completely recovered from the stego image when the secret data has been extracted, it is has drawn a lot of attentions from researchers. In this paper, a novel Taylor Expansion (TE) based stereo image reversible data hiding method is presented. Since the prediction accuracy is essential to the data hiding performance, a novel TE based predictor using correlations of two views of the stereo image is proposed. TE can fully exploit strong relationships between matched pixels in the stereo image so that the accuracy of the prediction can be improved. Then, histogram shifting is utilized to embed data to decrease distortion of stereo images, and multi-level hiding can increase embedding capacity. Experimental results show that the proposed method is superior to some existing data hiding methods considering embedding capacity and the quality of the stego stereo images.

scholarly journals An Effective Steganalysis Algorithm for Histogram-shifting Based Reversible Data Hiding

2020 ◽  
Vol 64 (1) ◽  
pp. 325-344
Author(s):  
Junxiang Wang ◽  
Lin Huang ◽  
Ying Zhang ◽  
Yonghong Zhu ◽  
Jiangqun Ni ◽  
...  
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting

Active steganalysis for histogram-shifting based reversible data hiding

2012 ◽  
Vol 285 (10-11) ◽  
pp. 2510-2518 ◽  
Author(s):  
Der-Chyuan Lou ◽  
Chao-Lung Chou ◽  
Hao-Kuan Tso ◽  
Chung-Cheng Chiu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Active Steganalysis
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