Reversible data hiding by adaptive group modification on histogram of prediction errors

Rad, Reza Moradi; Wong, KokSheik; Guo, Jing-Ming

doi:10.1016/j.sigpro.2016.02.001

Cited by 34 publications

(30 citation statements)

References 31 publications

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“…Rad et al [3] then produce a checkerboard predictor (CBP). It is able to generate more accurate PE histogram than MED.…”

Section: Related Workmentioning

confidence: 99%

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Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Islamy¹,

Ahmad²

2019

IJIES

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The transmitted information on the internet are prone to security concerns. To overcome this issue, some security methods have been developed in the last few decades. One of the reliable techniques to secure data is called data hiding. This method can be used in various multimedia data, like image, video, text, and audio. Histogram shifting (HS) is a reliable data hiding method used in digital images. It can preserve the similarity of the stego and original image; although, the amount of the protected data depends on the frequency of the most amount pixel in the original image. To solve this problem, we combine HS with prediction error (PE). By using the histogram generated by PE, the size of data that can be embedded increases. In the embedding phase, we do not shift the histogram, different from the existing methods. It is to maintain its original form as high as possible. Moreover, each PE value can contain more data. Based on the experimental result, the average increase in PSNR is 24.8075 dB for general images and 21.5625dB for medical images; while the average improvement of SSIM is 0.026823 and 0.022863 for general and medical images, respectively.

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“…Rad et al [3] then produce a checkerboard predictor (CBP). It is able to generate more accurate PE histogram than MED.…”

Section: Related Workmentioning

confidence: 99%

“…Many techniques have been developed in the last few decades. Broadly speaking, the method of steganography on spatial domains can be divided into compress-and-append, expansion (EB) and histogram shifting (HS) [3]. The compress-andappend method is widely used in the early days of the RDH method.…”

Section: Introductionmentioning

confidence: 99%

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Islamy¹,

Ahmad²

2019

IJIES

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“…However, the maximum embedding capacity is limited by the number of pixels at the peak of the histogram. To improve the embedding capacity, many scholars have performed further improvements based on HS technology in recent years [Qin, Chang, Huang et al (2013); Wang, Ye, Wang et al (2018); Rad, Wong and Guo (2016); Du, Yin and Zhang (2018)]. For example, Du et al [Du, Yin and Zhang (2018)] introduced the HS-based method in JPEG bitstream to optimize histogram modification.…”

Section: Introductionmentioning

confidence: 99%

Reversible Data Hiding Based on Pixel-Value-Ordering and Pixel Block Merging Strategy

Su¹,

Wang²,

Shen³

2019

Computers, Materials &Amp; Continua

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With the reversible data hiding method based on pixel-value-ordering, data are embedded through the modification of the maximum and minimum values of a block. A significant relationship exists between the embedding performance and the block size. Traditional pixel-value-ordering methods utilize pixel blocks with a fixed size to embed data; the smaller the pixel blocks, greater is the embedding capacity. However, it tends to result in the deterioration of the quality of the marked image. Herein, a novel reversible data hiding method is proposed by incorporating a block merging strategy into Li et al.'s pixel-value-ordering method, which realizes the dynamic control of block size by considering the image texture. First, the cover image is divided into non-overlapping 2×2 pixel blocks. Subsequently, according to their complexity, similarity and thresholds, these blocks are employed for data embedding through the pixel-value-ordering method directly or after being emerged into 2×4, 4×2, or 4×4 sized blocks. Hence, smaller blocks can be used in the smooth region to create a high embedding capacity and larger blocks in the texture region to maintain a high peak signal-to-noise ratio. Experimental results prove that the proposed method is superior to the other three advanced methods. It achieves a high embedding capacity while maintaining low distortion and improves the embedding performance of the pixel-value-ordering algorithm.

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“…Steganography is one of the most important techniques used to secure information [4]. Steganography is the art and science of hiding secret data within seemingly innocent carriers, which can be employed to achieve covert communications [5,6]. A steganographic system hides secret data into cover media (like text, image, audio, and video) and generates a stego-media [2], which is then sent to the receiver without anyone else knowing that it contains the hidden data [7].…”

Section: Introductionmentioning

confidence: 99%

A Novel Information Security System based on Steganography and Compression Techniques for Higher Education Institutions

Hosnia¹,

Ahmed²

2018

IJCA

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With the advancement of technology and the methods of information storage and exchange, the security of information and data became a vital issue for many institutions, especially higher education institutions. This paper introduces a novel and efficient information security system based on steganography and compression techniques to address the issues related to the security and efficient transmission of secret data in higher education institutions. In this system, the Lempel Ziv Welch (LZW) compression technique is used to compress the data to be hidden, to reduce their size and thereby reduce the percentage of distortion that may occur to the cover image. In addition, a new data hiding algorithm has been developed depending on the second bit, where data are hidden based on LSB without making any changes to the values of the second bit. If any changes are made, these will be only within LSB, which reduces the distortion in the cover image and increases the similarity between the cover image before and after hiding. In the retrieval stage, hidden data are retrieved from the second bit only. The proposed system performance was evaluated in terms of MSE (mean square of error), PSNR (peak signal-to-noise ratio), PD (pixel distortion) and BER (bit error rate). The experimental results confirm the efficiency of the proposed system that achieves good results with higher PSNR and lower MSE.

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Reversible data hiding by adaptive group modification on histogram of prediction errors

Cited by 34 publications

References 31 publications

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Reversible Data Hiding Based on Pixel-Value-Ordering and Pixel Block Merging Strategy

A Novel Information Security System based on Steganography and Compression Techniques for Higher Education Institutions

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