A Reversible Data Hiding for JPEG Images

2012 ◽  
Vol 433-440 ◽  
pp. 4615-4620 ◽  
Author(s):  
Gui Long Liao ◽  
Xin Peng Zhang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Rate Distortion ◽  
Previous Method ◽  
Data Embedding ◽  
Original Image ◽  
Secret Data ◽  
Jpeg Images ◽  
Efficient Data ◽  
Dct Coefficients

A novel reversible data hiding technique for JPEG images is proposed in this paper. Consecutive zeros in the tail of DCT coefficient sequence in each block are exploited to embed a number of secret bits by modifying only one coefficient. Thanks to the efficient data embedding in the DCT coefficients, the proposed scheme can provide a good rate-distortion performance. Also, when having an image containing secret data, one can perfectly recover the original image after extracting the embedded data. Experimental results show that the proposed scheme outperforms the previous method.

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.

An Efficient Reversible Data Hiding Scheme for Encrypted Images

2018 ◽  
Vol 10 (2) ◽  
pp. 1-22 ◽  
Author(s):  
Kai Chen ◽  
Dawen Xu
Keyword(s):  
Data Hiding ◽  
Efficient Method ◽  
Reversible Data Hiding ◽  
Additional Data ◽  
Emerging Technology ◽  
Experimental Results ◽  
Cover Image ◽  
Original Image ◽  
Secret Data ◽  
Encrypted Images

Reversible data hiding in the encrypted domain is an emerging technology, as it can preserve the confidentiality. In this article, an efficient method of reversible data hiding in encrypted images is proposed. The cover image is first partitioned into non-overlapping blocks. A specific modulo addition operation and block-scrambling operation are applied to obtain the encrypted image. The data-hider, who does not know the original image content, may reversibly embed secret data based on the homomorphic property of the cryptosystem. A scale factor is utilized for selecting embedding zone, which is scalable for different capacity requirements. At the receiving end, the additional data can be extracted if the receiver has the data-hiding key only. If the receiver has the encryption key only, he/she can recover the original image approximately. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original content without any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

Robust Reversible Data Hiding Scheme Based on Gravity Center Difference

2014 ◽  
Vol 6 (4) ◽  
pp. 14-33
Author(s):  
Qunting Yang ◽  
Tiegang Gao
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Original Image ◽  
Secret Data ◽  
Stego Image ◽  
Gravity Center ◽  
Hidden Data

This paper presents a robust reversible data hiding scheme in wavelet domain. The proposed scheme divides the permuted image into non-overlapping blocks and then gets sub-blocks. The generated sub-blocks are transformed by discrete wavelet transform and the corresponding low frequency regions are gotten, respectively. The gravity centers of low frequency regions in every non-overlapping block are very similar. These gravity center pairs are utilized to embed secret data since the insensitivity of the gravity centers to malicious tampering. Experimental results show that the original image can be recovered without any distortion after the hidden data have been extracted if the stego image has not been altered. Meanwhile hidden data can still be extracted without error when the image is compressed by JPEG and JPEG2000 to a certain extent. Compared with some existing literatures, the security, payload and robustness of the proposed scheme are significantly improved.

scholarly journals Code Division Multiplexing and Machine Learning Based Reversible Data Hiding Scheme for Medical Image

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Bin Ma ◽  
Bing Li ◽  
Xiao-Yu Wang ◽  
Chun-Peng Wang ◽  
Jian Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Medical Image ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Data Embedding ◽  
Secret Data ◽  
Spreading Sequences ◽  
Code Division Multiplexing

In this paper, a new reversible data hiding (RDH) scheme based on Code Division Multiplexing (CDM) and machine learning algorithms for medical image is proposed. The original medical image is firstly converted into frequency domain with integer-to-integer wavelet transform (IWT) algorithm, and then the secret data are embedded into the medium frequency subbands of medical image robustly with CDM and machine learning algorithms. According to the orthogonality of different spreading sequences employed in CDM algorithm, the secret data are embedded repeatedly, most of the elements of spreading sequences are mutually canceled, and the proposed method obtained high data embedding capacity at low image distortion. Simultaneously, the to-be-embedded secret data are represented by different spreading sequences, and only the receiver who has the spreading sequences the same as the sender can extract the secret data and original image completely, by which the security of the RDH is improved effectively. Experimental results show the feasibility of the proposed scheme for data embedding in medical image comparing with other state-of-the-art methods.

scholarly journals High-Capacity Reversible Data Hiding in Encrypted Images Based on Adaptive Predictor and Compression of Prediction Errors

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2166
Author(s):  
Bin Huang ◽  
Chun Wan ◽  
Kaimeng Chen
Keyword(s):  
Image Encryption ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Huffman Coding ◽  
Prediction Errors ◽  
Original Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Encrypted Images

Reversible data hiding in encrypted images (RDHEI) is a technology which embeds secret data into encrypted images in a reversible way. In this paper, we proposed a novel high-capacity RDHEI method which is based on the compression of prediction errors. Before image encryption, an adaptive linear regression predictor is trained from the original image. Then, the predictor is used to obtain the prediction errors of the pixels in the original image, and the prediction errors are compressed by Huffman coding. The compressed prediction errors are used to vacate additional room with no loss. After image encryption, the vacated room is reserved for data embedding. The receiver can extract the secret data and recover the image with no errors. Compared with existing approaches, the proposed method efficiently improves the embedding capacity.

scholarly journals Reversible Information Hiding Algorithm Based on Multikey Encryption

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhaohui Li ◽  
Yiqing Wang ◽  
Zhi Wang ◽  
Zheli Liu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Spatial Correlation ◽  
Data Hiding ◽  
Information Hiding ◽  
Reversible Data Hiding ◽  
Rate Distortion ◽  
Selection Method ◽  
Original Image ◽  
Embedding Capacity ◽  
Reversible Information Hiding ◽  
Encrypted Images

This paper proposes a scheme of reversible data hiding in encrypted images based on multikey encryption. There are only two parties that are involved in this framework, including the content owner and the recipient. The content owner encrypts the original image with a key set which is composed by a selection method according to the additional message. Thus, the image can be encrypted and embedded at the same time. Additional message can be extracted given that the recipient side could perform decryption strategy by exploiting spatial correlation; then, original image can be recovered without any loss. Compare with other current information hiding mechanism, the proposed approach provides higher embedding capacity and is also able to perfectly reconstruct the original image as well as the embedded message. Rate distortion of the proposed method outperforms the previously published ones.

scholarly journals Two-Dimensional Histogram Shifting-Based Reversible Data Hiding for H.264/AVC Video

2020 ◽  
Vol 10 (10) ◽  
pp. 3375
Author(s):  
Yuzhang Xu ◽  
Junhui He
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Great Success ◽  
Two Dimensional ◽  
Histogram Shifting ◽  
File Size ◽  
Secret Data ◽  
Embedding Efficiency ◽  
Dct Coefficients ◽  
Dct Coefficient

Histogram shifting (HS) has been proved to be a great success in reversible data hiding (RDH). To reduce the quality loss of marked media and the increase in file size, several two-dimensional (2D) HS schemes based on the characteristics of cover media have been proposed recently. However, our analysis shows that the embedding strategies used in these methods can be further optimized. In this paper, two new 2D HS schemes for RDH in H.264/AVC video are developed, one of which uses the DCT coefficient pairs with both values 0 and the other does not. The embedding efficiency of a DCT coefficient pair in different embedding modes is firstly calculated. Then, based on the obtained embedding efficiency along with the statistical distribution of DCT coefficient pairs, two better embedding strategies are proposed. The secret data is finally embedded into the pairs of DCT coefficients of the middle and high frequencies using our proposed strategies. The comparison experiment results demonstrate that our schemes can achieve enhanced visual quality in terms of PSNR, SSIM, and entropy in most cases, and the increase in file size is smaller.

scholarly journals Histogram Based Data Cryptographic Technique with High Level Security

2019 ◽  
Vol 8 (04) ◽  
pp. 08-14
Author(s):  
Prof. Romi Morzelona
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Original Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Bit Rate ◽  
Secret Data ◽  
Additional Information ◽  
High Level ◽  
Embedding Function

Histogram shifting plays a major role in reversible data hiding technique. By this shifting method the distortion is reduced and the embedding capacity may be increased. This proposed work uses, shifting and embedding function. The pixel elements of the original image are divided into two disjoint groups. The first group is used to carry the secret data and the second group adds some additional information which ensures the reversibility of data. The  parameter such as PSNR, embedding capacity and bit rate are used for comparisons of various images

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