Reversible data hiding using multi-pass pixel-value-ordering and pairwise prediction-error expansion

He, Weiji; Xiong, Ge; Weng, Shaowei; Cai, Zhanchuan; Wang, Yaomin

doi:10.1016/j.ins.2018.04.088

Cited by 65 publications

(59 citation statements)

References 38 publications

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“…For Barbara, Boat and Lake, it is noticeable our proposed scheme can achieve comparable embedding performance for higher payloads when compared with KPPE. Therefore, we conclude our proposed method can still achieve comparable or better embedding performance than the papers [9], [23]- [27].…”

Section: A Comparison With K-pass Pvo Based Techniquementioning

confidence: 60%

“…COMPARISON OF PAYLOAD AND IMAGE QUALITY MEASURED BY PSNR Fig. 3 shows the marked image quality of the eight test images measured by PSNR when k-pass PVO [26], PVO-k [25], IPVO [24], PVO [23], KPPE [27] and Sachnev et al's method [9] are applied.…”

Section: A Comparison With K-pass Pvo Based Techniquementioning

confidence: 99%

“…Recently, He et al have proposed an RDH technique named KPPE [27], which combines k-pass PVO with pairwise PEE. Pairwise PEE helps KPPE to largely improve embedding performance by avoiding two adjacent embeddable prediction-errors being simultaneously increased or decreased by 1.…”

Section: A Comparison With K-pass Pvo Based Techniquementioning

confidence: 99%

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Improved K-Pass Pixel Value Ordering Based Data Hiding

Weng

Chen

et al. 2019

IEEE Access

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K-pass pixel value ordering (PVO) is an effective reversible data hiding (RDH) technique. In k-pass PVO, the complexity measurement may lead to a weak estimation result because the unaltered pixels in a block are excluded to estimate block complexity. In addition, the prediction-error is computed without considering the location relationship of the second largest and largest pixels or the second smallest and smallest pixels. To this end, an improved RDH technique is proposed in this paper to enhance the embedding performance. The improvement mainly lies in the following two aspects. First, some pixels in a block, which are excluded from data hiding in some existing RDH methods, are exploited together with the neighborhood surrounding this block to increase the estimation accuracy of local complexity. Second, the remaining pixels in a block, i.e., three largest and three smallest pixels are involved in data embedding. Taking three largest pixels for example, when the difference between the largest and third largest pixels is relatively large (e.g., > 1), we improve k-pass PVO by considering the location relationship of the second largest and largest pixels. The advantage of doing this is that the difference valued 3 between the maximum and the second largest pixel which is shifted in k-pass PVO, is able to carry 1 bit data in our method. In other words, a larger amount of pixels are able to carry data bits in our scheme compared with k-pass PVO. Abundant experimental results reveal that the proposed method achieves preferable embedding performance compared with the previous work, especially when a larger payload is required. INDEX TERMS K-pass PVO, reversible data hiding, relative location, complexity measurement.

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Section: A Comparison With K-pass Pvo Based Techniquementioning

confidence: 60%

Section: A Comparison With K-pass Pvo Based Techniquementioning

confidence: 99%

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Improved K-Pass Pixel Value Ordering Based Data Hiding

Weng

Chen

et al. 2019

IEEE Access

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“…Later, Alattar [19] modified Tian's technique to improve the HC using four pixels based two-fold expansion technique. Improved and advanced DE based techniques [20,21] were proposed by many authors. However, these techniques were experienced in limited HC.…”

Section: Introductionmentioning

confidence: 99%

Dual Stego-imaging Based Reversible Data Hiding Using Improved LSB Matching

Sahu¹,

Swain²

2019

IJIES

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Since the inception of the reversible data hiding (RDH) concept, it has been a compelling topic in the field of data hiding. Being reversible, it has the ability to restore the original image followed by the successful retrieval of the secret data, at the receiving side. The concept of the dual stego-image based RDH technique utilizes two identical images of the original image for concealing the secret data, has gained wide compliance. Therefore, someone with both the stego-images can only extract the concealed data. In this paper, two improved dual imaging based RDH techniques, such as (1) dual stego-image based pixel pair LSB matching with reversibility, and (2) dual stego-image based modified LSB matching with reversibility, are proposed. In technique 1, at first two mirrored images are obtained from the original image. Then, using the pair of two consecutive pixels from the original image, the mirrored images pixels are modified using LSB matching technique. Later, these pixel pairs are readjusted to ensure reversibility at the receiving side. Similarly, technique 2 utilizes each original pixel to generate two distinct stegopixels using modified LSB matching. The experimental result shows that the technique 1 maintains excellent peak signal-to-noise ratio (PSNR) of 51.29 dB and 51.30 dB for the two stego-images with hiding capacity (HC) of 524288 bits. At the same time, technique 2 offers 51.19 dB and 49.44 dB of PSNR while exhibiting the equal HC. Further, investigation with various image quality assessment (IQA) metrics like quality index (QI), and structural similarity index (SSIIM) are proven to be competent over the other existing works considered in this paper. In addition, both the proposed techniques have shown excellent anti-steganalytic ability against RS and pixel difference histogram (PDH) attack.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Lei Wei . compression based [20]- [24] and difference expansion (DE) based [10]- [12], [25]- [28]. Recently, a popular RDH application is to embed management information into personal images stored on cloud server.…”

Section: Introductionmentioning

confidence: 99%

A New High Capacity Separable Reversible Data Hiding in Encrypted Images Based on Block Selection and Block-Level Encryption

Wang

Cai

2019

IEEE Access

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Reversible data hiding in encrypted image (RDHEI) is a technology that can simultaneously implement privacy protection and reversible information hiding. For RDHEI, the main problem is the conflict between embedding capacity and real reversibility. In this paper, to solve such a conflict, a new block-level image encryption method is proposed to fulfill privacy protection while preserving the spatial correlation of pixels inside pixel block. On this basis, a new reversible data hiding method based on block selection is also proposed. Specifically, pixel blocks are classified into embeddable block (EB) and non-embeddable block (NEB). Then, additional data is embedded into only EBs and the position file locating EB is also embedded using a new self-embedding method. Experimental results demonstrate that the proposed method not only achieves high embedding capacity, but also guarantees lossless data extraction and perfect image recovery. INDEX TERMS Image encryption, reversible data hiding, real reversibility, block selection, high capacity.

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Reversible data hiding using multi-pass pixel-value-ordering and pairwise prediction-error expansion

Cited by 65 publications

References 38 publications

Improved K-Pass Pixel Value Ordering Based Data Hiding

Improved K-Pass Pixel Value Ordering Based Data Hiding

Dual Stego-imaging Based Reversible Data Hiding Using Improved LSB Matching

A New High Capacity Separable Reversible Data Hiding in Encrypted Images Based on Block Selection and Block-Level Encryption

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