A Comprehensive Study of Reversible Data Hiding (RDH) Schemes Based on Pixel Value Ordering (PVO)

Kaur, Gurjinder; Singh, Samayveer; Rani, Rajneesh; Kumar, Rajeev

doi:10.1007/s11831-020-09512-3

“…Reversible data hiding (RDH) has received great attention recently in the field of information hiding Security and Communication Networks [22,[31][32][33][34]. A significant challenge in RDH-based techniques is increasing the data hiding capacity along with image quality [31]. Singh in [22] proposed a new data hiding scheme using a mixture of adaptive pixel value differencing (PVD) [35] and LSB in order to increase the data hiding capacity.…”

Section: Related Workmentioning

confidence: 99%

A New Method of Coding for Steganography Based on LSB Matching Revisited

Fateh

¹

,

Rezvani

²

,

Irani

³

2021

Security and Communication Networks

View full text Add to dashboard Cite

LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this method works only for n = 2 , where n is the number of bits in a block of the secret message. In this paper, we propose an improved version of the LSB matching revisited approach, which works for n > 2 . The proposed scheme contains two phases including embedding and extracting the message. In the embedding phase, we first convert the secret message into a bit-stream, and then the bit-stream is divided into a set of blocks including n bits in each block. Then we choose 2 n − 1 pixels for hiding such n bits of the secret message. In the next step, we choose the operations needed to generate such a message. Finally, we perform the obtained operations over the coefficients to hide the secret message. The proposed approach needs fewer changes than LSB MR when n > 2 . The capacity of the proposed approach is 2 n − 1 / 2 n − 1 − 1 × 100 % higher than the F5 method where this value for n > 2 is bigger than 75%. For example, the capacity of our scheme is 75% higher than the capacity of F5 for n = 3 . The proposed method can be used in the first step of every steganography method to reduce the change in the stego image. Therefore, this method is a new coding method for steganography. Our experimental results using steganalysis show that using our method provides around 10% higher detection error for SRNet over two steganography schemes.

show abstract

“…Dragoi et al [39] also proposed an improved pairwise PVO-based method in which the blocks are classified on the basis of a local complexity measure, smooth blocks are processed using pairwise PVO, slightly noisy blocks using standard PVO while complex blocks are kept unchanged. Most of the above mentioned PVO methods have been surveyed in [40]. To increase the EC, Kumar et al proposed two new reversible data hiding schemes using PVO based methods [41,42].…”

Section: Related Workmentioning

confidence: 99%

High‐quality reversible data hiding scheme using sorting and enhanced pairwise PEE

Kaur

¹

,

Singh

²

,

Rani

³

et al. 2021

IET Image Processing

Self Cite

View full text Add to dashboard Cite

This paper proposes a novel reversible data hiding (RDH) technique using sorting and pairwise prediction error expansion (PEE) to improve embedding capacity (EC) while retaining the quality of cover image. The proposed scheme traverses alternate pixels of the cover image in a zig‐zag order to construct two independent sets for sequential embedding. The pixels of each set are sorted in an increasing order of their rhombus mean followed by a two‐pass data embedding by dividing the sets into 1 × 3 size blocks based on some pre‐defined criteria. In pass 1, two prediction errors are calculated for the first and the last pixels using their rhombus means; and pairwise mapping is modified and exploited to embed the secret data in such a way that the value of the first pixel is either increased or remains unchanged, and the value of the last pixel is either decreased or remains unchanged. In pass‐2, the middle pixel is utilised to predict the first and last pixels and the values of the first pixel and the last pixel are either decreased or remains unchanged and either increased or remains unchanged, respectively. In contrast to some existing recovery‐based methods, the proposed pass‐2 guarantees to complement the changes made in pass‐1, thereby boosting the quality along with increased EC. The experimental results show that the proposed method achieves better embedding performance than the state‐of‐the‐art RDH techniques. More specifically, the proposed method gets an increment by an average of 0.46 dB and 1.01 dB for embedding 10,000 bits and 20,000 bits respectively over its closest prior art.

show abstract

“…Through more than 20 years of development, RDH has made great progress in reversibility and capacity. Nowadays, the focus of research mainly lies in high‐fidelity RDH [1] and RDH for encrypted media [2].…”

Section: Introductionmentioning

confidence: 99%

Reversible data hiding based on multi‐predictor and adaptive expansion

He

¹

,

Xiong

²

,

Wang

³

2021

IET Image Processing

1

0

View full text Add to dashboard Cite

Adaptive embedding plays an important role in improving the embedding performance of reversible data hiding and it is usually realized by modifying the prediction‐errors discriminately. By extending the skewed histogram shifting technique which uses a pair of extreme predictions to determine whether the target pixel should be predicted or not, this paper realizes another form of adaptive embedding, that is, adaptive prediction‐error generation. Specifically, it is proposed to adaptively determine the pair of extreme predictions according to image content. Each pair of extreme predictions is first evaluated by the introduced distortion per embedding one bit. Then, an efficient mechanism to determine the best pair of extreme predictions for pixels with a given local complexity is designed. With such a mechanism solving the computational problem, it is also proposed to extend the context to obtain more pairs of extreme predictions such that more precise multi‐predictor can be realized. With obtained errors, the best expansion bins are determined to achieve a more comprehensive self‐adaption. Experimental results demonstrate that the proposed scheme achieves better capacity‐distortion performance and outperforms a series of state‐of‐the‐art schemes.

show abstract

A Comprehensive Study of Reversible Data Hiding (RDH) Schemes Based on Pixel Value Ordering (PVO)

Cited by 33 publications

References 71 publications

A New Method of Coding for Steganography Based on LSB Matching Revisited

A New Method of Coding for Steganography Based on LSB Matching Revisited

High‐quality reversible data hiding scheme using sorting and enhanced pairwise PEE

Reversible data hiding based on multi‐predictor and adaptive expansion

Contact Info

Product

Resources

About