A Novel Method for High Capacity Reversible Data Hiding Scheme Using Difference Expansion

2019 ◽  
Vol 8 (4) ◽  
pp. 13-27
Author(s):  
Subhadip Mukherjee ◽  
Biswapati Jana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
High Capacity ◽  
Correlation Coefficients ◽  
Extraction Process ◽  
Research Area ◽  
Difference Expansion ◽  
Secret Data ◽  
Hiding Capacity

Data hiding techniques are very significant in the research area of information security. In this article, the authors propose a new reversible data hiding (RDH) scheme using difference expansion. At first, the original image is partitioned into 3 × 3 pixel blocks, then marked Type-one and Type-two pixels based on their coordinate values. After that, the authors find correlated pixels by computing correlation coefficients and the median of Type-one pixels. Next, secret data bits are embedded within Type-two pixels based on correlated pixels and Type-one pixels based on the stego Type-two pixels. The data extraction process successfully extracts secret data as well as recovers the cover image. The authors observed the effects of the proposed method by performing experiments on some standard cover images and found significantly better result in terms of data hiding capacity compared with existing data hiding schemes.

scholarly journals High-Payload Data-Hiding Method for AMBTC Decompressed Images

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 145
Author(s):  
Jung-Yao Yeh ◽  
Chih-Cheng Chen ◽  
Po-Liang Liu ◽  
Ying-Hsuan Huang
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Cover Image ◽  
Secret Data ◽  
Perceptual Distortion ◽  
Hiding Capacity ◽  
High Data ◽  
Capacity Data ◽  
High Payload ◽  
Better Than

Data hiding is the art of embedding data into a cover image without any perceptual distortion of the cover image. Moreover, data hiding is a very crucial research topic in information security because it can be used for various applications. In this study, we proposed a high-capacity data-hiding scheme for absolute moment block truncation coding (AMBTC) decompressed images. We statistically analyzed the composition of the secret data string and developed a unique encoding and decoding dictionary search for adjusting pixel values. The dictionary was used in the embedding and extraction stages. The dictionary provides high data-hiding capacity because the secret data was compressed using dictionary-based coding. The experimental results of this study reveal that the proposed scheme is better than the existing schemes, with respect to the data-hiding capacity and visual quality.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Chunqiang Yu ◽  
Xianquan Zhang ◽  
Zhenjun Tang ◽  
Yan Chen ◽  
Jingyu Huang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Visual Quality ◽  
Input Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Encrypted Image ◽  
High Embedding Capacity ◽  
Additive Homomorphism

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.

scholarly journals Two-Bit Embedding Histogram-Prediction-Error Based Reversible Data Hiding for Medical Images with Smooth Area

Computers ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 152
Author(s):  
Ching-Yu Yang ◽  
Ja-Ling Wu
Keyword(s):  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Medical Images ◽  
High Capacity ◽  
Personal Privacy ◽  
Hiding Capacity ◽  
X Ray ◽  
Magnetic Resonance Imaging Mri ◽  
Hidden Data

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep medical images or health information secret unless they have permission from the data owner to disclose them. Reversible data hiding (RDH) is a technique that embeds metadata into an image and can be recovered without any distortion after the hidden data have been extracted. This work aims to develop a fully reversible two-bit embedding RDH algorithm with a large hiding capacity for medical images. Medical images can be partitioned into regions of interest (ROI) and regions of noninterest (RONI). ROI is informative with semantic meanings essential for clinical applications and diagnosis and cannot tolerate subtle changes. Therefore, we utilize histogram shifting and prediction error to embed metadata into RONI. In addition, our embedding algorithm minimizes the side effect to ROI as much as possible. To verify the effectiveness of the proposed approach, we benchmarked three types of medical images in DICOM format, namely X-ray photography (X-ray), computer tomography (CT), and magnetic resonance imaging (MRI). Experimental results show that most of the hidden data have been embedded in RONI, and the performance achieves high capacity and leaves less visible distortion to ROIs.

scholarly journals A Reversible Data Hiding Method in Encrypted Images for Controlling Trade-Off between Hiding Capacity and Compression Efficiency

2021 ◽  
Vol 7 (12) ◽  
pp. 268
Author(s):  
Ryota Motomura ◽  
Shoko Imaizumi ◽  
Hitoshi Kiya
Keyword(s):  
Data Hiding ◽  
Image Coding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Lossless Compression ◽  
The Other ◽  
Compression Efficiency ◽  
Hiding Capacity ◽  
Encrypted Images ◽  
New Framework

In this paper, we propose a new framework for reversible data hiding in encrypted images, where both the hiding capacity and lossless compression efficiency are flexibly controlled. There exist two main purposes; one is to provide highly efficient lossless compression under a required hiding capacity, while the other is to enable us to extract an embedded payload from a decrypted image. The proposed method can decrypt marked encrypted images without data extraction and derive marked images. An original image is arbitrarily divided into two regions. Two different methods for reversible data hiding in encrypted images (RDH-EI) are used in our method, and each one is used for either region. Consequently, one region can be decrypted without data extraction and also losslessly compressed using image coding standards even after the processing. The other region possesses a significantly high hiding rate, around 1 bpp. Experimental results show the effectiveness of the proposed method in terms of hiding capacity and lossless compression efficiency.

scholarly journals Reversible data hiding scheme based on pixel-value differencing in dual images

2020 ◽  
Vol 16 (7) ◽  
pp. 155014772091100
Author(s):  
Pyung-Han Kim ◽  
Kwan-Woo Ryu ◽  
Ki-Hyun Jung
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Cover Image ◽  
Maximum Difference ◽  
Secret Data ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
Dual Images

In this article, a new reversible data hiding scheme using pixel-value differencing in dual images is proposed. The proposed pixel-value differencing method can embed more secret data as the difference value of adjacent pixels is increased. In the proposed scheme, the cover image is divided into non-overlapping blocks and the maximum difference value is calculated to hide secret bits. On the sender side, the length of embeddable secret data is calculated by using the maximum difference value and the log function, and the decimal secret data are embedded into the two stego-images after applying the ceil function and floor function. On the receiver side, the secret data extraction and the cover image restoration can be performed by using the correlation between two stego-images. After recovering the cover image from two stego-images, the secret data can be extracted using the maximum difference value and the log function. The experimental results show that the proposed scheme has a higher embedding capacity and the proposed scheme differs in embedding the secret data depending on the characteristics of the cover image with less distortion. Also, the proposed scheme maintains the degree of image distortion that cannot be perceived by the human visual system.

scholarly journals Implementation of Block-Based Hierarchical Prediction for Developing an Error-Propagation-Free Reversible Data Hiding Scheme

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1146 ◽  
Author(s):  
Hu ◽  
Lo ◽  
Wu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Error Propagation ◽  
Prediction Errors ◽  
Secret Data ◽  
Image Block ◽  
Hiding Capacity ◽  
Block Based ◽  
Prediction Mechanism ◽  
Embedded Image

This paper proposes a reversible data hiding technique based on the residual histogram shifting technique. To improve the hiding capacity, this study proposes a multiple-round hierarchical prediction mechanism that generates the prediction errors of each image block. The prediction errors of each block are collected to produce the residual histogram and the secret data are then embedded into the residual histogram to obtain the embedded image. Experimental results demonstrate that the proposed technique not only provides good hiding capacity, but also maintains good image quality of the embedded image. In addition, this technique can be easily extended for image integrity protection as it is capable of resisting error propagation.

A high capacity reversible data hiding scheme with edge prediction and difference expansion

2009 ◽  
Vol 82 (12) ◽  
pp. 1966-1973 ◽  
Author(s):  
Hsien-Chu Wu ◽  
Chih-Chiang Lee ◽  
Chwei-Shyong Tsai ◽  
Yen-Ping Chu ◽  
Hung-Ruei Chen
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Difference Expansion

scholarly journals High Capacity Reversible Data Hiding Based on the Compression of Pixel Differences

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1435
Author(s):  
Kai-Meng Chen
Keyword(s):  
Spatial Correlation ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Visual Quality ◽  
Small Range ◽  
Encryption Scheme ◽  
Secret Data ◽  
Encrypted Image ◽  
Block Level

In this paper, we proposed a novel reversible data hiding method in encrypted image (RDHEI), which is based on the compression of pixel differences. In the proposed method, at the content owner’ side the image is divided into non-overlapping blocks, and a block-level image encryption scheme is used to generate the encrypted image, which partially retains spatial correlation in the blocks. Due to the spatial correlation, in each block the pixels are highly likely to be similar. Therefore, the pixel differences in all blocks are concentrated in a small range and can be compressed. By the compression of pixel differences, the data hider can vacate the room to accommodate secret data in the encrypted image without losing information. At the receiver’s side, the receiver can obtain secret data or retrieve the original image using different keys with no error. The experimental results demonstrate that, compared with existing methods, the proposed method can achieve a higher capacity and visual quality.

scholarly journals PVO-Based Reversible Data Hiding Exploiting Two-Layer Embedding for Enhancing Image Fidelity

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1164
Author(s):  
Chin-Feng Lee ◽  
Jau-Ji Shen ◽  
Yi-Jhen Wu ◽  
Somya Agrawal
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Block Size ◽  
Threshold Value ◽  
Difference Expansion ◽  
Secret Data ◽  
Prediction Error Expansion ◽  
Previous State ◽  
Pixel Value ◽  
Fixed Embedding

Recently, Li et al. proposed a data hiding method based on pixel value ordering (PVO) and prediction error expansion (PEE). In their method, maximum and minimum values were predicted and the pixel values were modified to embed secret data. Thereafter, many scholars have proposed improvisations to the original PVO method. In this paper, a Reversible data hiding (RDH) method is proposed where the secret data is dispersed into two layers using different modes of operations. The second layer changes the dividing mode, and the first and the second layers do not take duplicate blocks. Under a fixed embedding capacity, threshold value and block size are controlled, complex blocks are filtered and the secret data is hidden in smooth blocks. This paper also compares the effectiveness of four well-known PVO series methods, the latest PVO methods, difference expansion (DE) method and reduced difference expansion (RDE) method. Experimental results show that the proposed method reduces distortion in the image, thereby enhancing the visual symmetry/quality compared to previous state-of-the-art methods and increasing its high application value.

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