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 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 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.

A high payload separable reversible data hiding in cipher image with good decipher image quality

2020 ◽  
Vol 38 (5) ◽  
pp. 6403-6414 ◽  
Author(s):  
R. Anushiadevi ◽  
Padmapriya Pravinkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Payload

Reversible Data Hiding for DNA Sequences and Its Applications

2014 ◽  
Vol 6 (4) ◽  
pp. 1-13 ◽  
Author(s):  
Qi Tang ◽  
Guoli Ma ◽  
Weiming Zhang ◽  
Nenghai Yu
Keyword(s):  
Data Hiding ◽  
Dna Sequences ◽  
Reversible Data Hiding ◽  
Tamper Detection ◽  
Dna Databases ◽  
Living Things ◽  
Embedding Rate

As the blueprint of vital activities of most living things on earth, DNA has important status and must be protected perfectly. And in current DNA databases, each sequence is stored with several notes that help to describe that sequence. However, these notes have no contribution to the protection of sequences. In this paper, the authors propose a reversible data hiding method for DNA sequences, which could be used either to embed sequence-related annotations, or to detect and restore tampers. When embedding sequence annotations, the methods works in low embedding rate mode. Only several bits of annotations are embedded. When used for tamper detection and tamper restoration, all possible embedding positions are utilized to assure the maximum restoration capacity.

scholarly journals An Improved Reversible Image Transformation Using K-Means Clustering and Block Patching

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 17 ◽  
Author(s):  
Haidong Zhong ◽  
Xianyi Chen ◽  
Qinglong Tian
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Privacy Protection ◽  
Reversible Data Hiding ◽  
Auxiliary Information ◽  
Experimental Results ◽  
Image Transformation ◽  
Clustering Method ◽  
Stego Image ◽  
Encrypted Images

Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in image privacy protection and reversible data hiding in encrypted images. However, the amount of accessorial information, for recording the transformation parameters, is very large in the traditional RIT method, which results in an abrupt degradation of the stego-image quality. In this paper, an improved RIT method for reducing the auxiliary information is proposed. Firstly, we divide secret and target images into non-overlapping blocks, and classify these blocks into K classes by using the K-means clustering method. Secondly, we match blocks in the last (K-T)-classes using the traditional RIT method for a threshold T, in which the secret and target blocks are paired with the same compound index. Thirdly, the accessorial information (AI) produced by the matching can be represented as a secret segment, and the secret segment can be hided by patching blocks in the first T-classes. Experimental results show that the proposed strategy can reduce the AI and improve the stego-image quality effectively.

scholarly journals Reversible Data Hiding in a Chaotic Encryption Domain Based on Odevity Verification

2021 ◽  
Vol 13 (6) ◽  
pp. 1-14
Author(s):  
Lianshan Liu ◽  
Xiaoli Wang ◽  
Lingzhuang Meng ◽  
Gang Tian ◽  
Ting Wang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Chaotic Encryption ◽  
Original Image ◽  
Embedding Capacity ◽  
Logistic Mapping ◽  
Henon Mapping ◽  
Pixel Value ◽  
Carrier Image

On the premise of guaranteeing the visual effect, in order to improve the security of the image containing digital watermarking and restore the carrier image without distortion, reversible data hiding in chaotic encryption domain based on odevity verification was proposed. The original image was scrambled and encrypted by Henon mapping, and the redundancy between the pixels of the encrypted image was lost. Then, the embedding capacity of watermarking can be improved by using odevity verification, and the embedding location of watermarking can be randomly selected by using logistic mapping. When extracting the watermarking, the embedded data was judged according to the odevity of the pixel value of the embedding position of the watermarking, and the carrier image was restored nondestructively by odevity check image. The experimental results show that the peak signal-to-noise ratio (PSNR) of the original image is above 53 decibels after the image is decrypted and restored after embedding the watermarking in the encrypted domain, and the invisibility is good.

Reversible data hiding method based on pixel expansion and homomorphic encryption

2020 ◽  
Vol 39 (3) ◽  
pp. 2977-2990
Author(s):  
R. Anushiadevi ◽  
Padmapriya Praveenkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Homomorphic Encryption ◽  
Secret Message ◽  
Pixel Expansion ◽  
Stego Image ◽  
Encrypted Image ◽  
Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

On Performance Improvement Of Reversible Data Hiding With Contrast Enhancement

2020 ◽  
Vol 63 (10) ◽  
pp. 1584-1596
Author(s):  
Haishan Chen ◽  
Junying Yuan ◽  
Wien Hong ◽  
Jiangqun Ni ◽  
Tung-Shou Chen
Keyword(s):  
Contrast Enhancement ◽  
Performance Improvement ◽  
Data Hiding ◽  
Upper Bound ◽  
Reversible Data Hiding ◽  
Image Contrast ◽  
Embedding Capacity ◽  
Visible Image ◽  
Multiple Cycles ◽  
Embedding Rate

Abstract Reversible data hiding (RDH) with contrast enhancement (RDH-CE) is a special type of RDH in improving the subjective visual perception by enhancing the image contrast during the process of data embedding. In RDH-CE, data hiding is achieved via pairwise histogram expansion, and the embedding rate can be increased by performing multiple cycles of histogram expansions. However, when embedding rate gets high, human visible image degradation is observed. Previous work designed an upper bound of the embedding level for RDH-CE, which effectively avoids image over-sharping but offers limited embedding capacity. In this paper, a better tunable bound is designed to enhance the embedding capacity of RDH-CE by exploiting the characteristics of histogram distribution. Furthermore, the objective distortion introduced by histogram pre-shifting is minimized when the embedding level is no more than the upper bound, and the human visible degradation is minimized when the embedding level exceeds the limitation of the proposed upper bound. Experimental results validate that the proposed method provides appropriate upper bound of the embedding level, increases the effective embedding capacity and offers better image contrast.

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