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.

Block-Based Reversible Data Hiding Using Histogram Shifting and Modulus Operator for Digital Images

2017 ◽  
Vol 26 (06) ◽  
pp. 1750103 ◽  
Author(s):  
Pankaj Garg ◽  
Singara Singh Kasana ◽  
Geeta Kasana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Signal To Noise ◽  
Secret Data ◽  
Peak Points ◽  
Block Based

A Reversible Data Hiding technique by using histogram shifting and modulus operator is proposed in which secret data is embedded into blocks of the cover image. These blocks are modified by using modulus operator to increase the number of peak points in the histogram of the cover image which further increases its embedding capacity. Secret data is embedded in the original cover blocks of the cover image by using peak points of the predicted blocks, which are generated by using modulus operator. Peak Signal to Noise Ratio and PSNR-Human Visual System are used to show the human visual acceptance of the proposed technique. Experimental results show that the embedding capacity is high as compared to the capacity of existing RDH techniques, while distortion in marked images is also less as compared to distortion produced by these existing techniques.

scholarly journals Histogram-based multilayer reversible data hiding method for securing secret data

2019 ◽  
Vol 8 (3) ◽  
pp. 1128-1134
Author(s):  
Chaidir Chalaf Islamy ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Histogram Shifting ◽  
Secret Data ◽  
Stego Image ◽  
Sensitive Data ◽  
Modern Age ◽  
Potential Methods

In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.

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 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

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 Reversible Data Hiding in Encrypted Images Using Median Edge Detector and Two’s Complement

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 921
Author(s):  
Rui Wang ◽  
Guohua Wu ◽  
Qiuhua Wang ◽  
Lifeng Yuan ◽  
Zhen Zhang ◽  
...  
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Personal Information ◽  
Rapid Development ◽  
Prediction Method ◽  
Prediction Errors ◽  
Edge Detector ◽  
Secret Data ◽  
Encrypted Images ◽  
Cloud Servers

With the rapid development of cloud storage, an increasing number of users store their images in the cloud. These images contain many business secrets or personal information, such as engineering design drawings and commercial contracts. Thus, users encrypt images before they are uploaded. However, cloud servers have to hide secret data in encrypted images to enable the retrieval and verification of massive encrypted images. To ensure that both the secret data and the original images can be extracted and recovered losslessly, researchers have proposed a method that is known as reversible data hiding in encrypted images (RDHEI). In this paper, a new RDHEI method using median edge detector (MED) and two’s complement is proposed. The MED prediction method is used to generate the predicted values of the original pixels and calculate the prediction errors. The adaptive-length two’s complement is used to encode the most prediction errors. To reserve room, the two’s complement is labeled in the pixels. To record the unlabeled pixels, a label map is generated and embedded into the image. After the image has been encrypted, it can be embedded with the data. The experimental results indicate that the proposed method can reach an average embedding rate of 2.58 bpp, 3.04 bpp, and 2.94 bpp on the three datasets, i.e., UCID, BOSSbase, BOWS-2, which outperforms the previous work.

scholarly journals A Location Map Reduced Reversible Data Hiding Method Using Prediction Error Modification

2012 ◽  
Vol 6-7 ◽  
pp. 428-433
Author(s):  
Yan Wei Li ◽  
Mei Chen Wu ◽  
Tung Shou Chen ◽  
Wien Hong
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Cover Image ◽  
Prediction Errors ◽  
Secret Data ◽  
Location Map ◽  
Comparable Image Quality

We propose a reversible data hiding technique to improve Hong and Chen’s (2010) method. Hong and Chen divide the cover image into pixel group, and use reference pixels to predict other pixel values. Data are then embedded by modifying the prediction errors. However, when solving the overflow and underflow problems, they employ a location map to record the position of saturated pixels, and these pixels will not be used to carry data. In their method, if the image has a plenty of saturated pixels, the payload is decreased significantly because a lot of saturated pixels will not joint the embedment. We improve Hong and Chen’s method such that the saturated pixels can be used to carry data. The positions of these saturated pixels are then recorded in a location map, and the location map is embedded together with the secret data. The experimental results illustrate that the proposed method has better payload, will providing a comparable image quality.

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