High capacity reversible data hiding scheme based on residual histogram shifting for block truncation coding

Chang, I-Cheng; Hu, Yu‐Chen; Chen, Wu‐Lin; Lo, Chieh

doi:10.1016/j.sigpro.2014.09.036

Cited by 48 publications

(39 citation statements)

References 25 publications

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“…As the degree of freedom is always greater than 30, chi-square statistics will not be found from a chi-squared table. Therefore, the chi-squared distributions are approximated from the normal distribution by Equation (19). …”

Section: Chi-square Testmentioning

confidence: 99%

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Enhancing the Performance of the Data Embedment Process through Encoding Errors

Kamal

Islam

2016

Electronics

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Abstract:Image steganography is a multipurpose-serving key emerging technology that is used for covertly transferring, storing, and governing various digital data, including intellectual properties and copyrights, social media data, multimedia data, and secrets of law-enforcing agencies. During the management in the stated information, nowadays, massive amounts of data are handled that require greater security. For that purpose, data are embedded into a cover image to hide them from any intruders. Nevertheless, the requirements of a larger embedding capacity, improved stego-image quality, and reduced time complexity is increasing. In this paper, the authors have presented a novel data-embedding scheme where the prediction error-based data-hiding scheme is modified in an intricate way so that all the image pixels can accept secret bits. A distance matrix between the pixel values of each image block and a reference value are measured first. Thereafter, the distances are encoded into two states: 1 and −1. That encoding process enables the scheme to implant one bit in every pixel of the cover image. During the bit implantation, the errors 1 and −1 are modified by shifting them to the right and left directions, respectively. This strategy enhances the embedding capacity by a factor of more than 2. The use of reference values reduces the computational complexity notably, and in the meanwhile increases the security and robustness of the scheme because the reference values are not open to any third party. The scheme also reduces the time complexity by 2-16 times with compared to its competing schemes. Experimental results prove the superiority of the proposed algorithm on embedding capacity, visual quality, and time complexity compared to the current well-accepted existing schemes.

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Section: Chi-square Testmentioning

confidence: 99%

“…Therefore, the chi-squared distributions are approximated from the normal distribution by Equation (19).…”

Section: Chi-square Testmentioning

confidence: 99%

Enhancing the Performance of the Data Embedment Process through Encoding Errors

Kamal

Islam

2016

Electronics

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“…While, a reversible data hiding scheme allows the extractor to recover the original cover media completely upon extraction of the hidden data. In the recent past, several reversible data hiding schemes have been developed based on different concepts such as lossless compression [31], difference expansion [1,112], histogram-shifting [16,30,36,40,65,96,100,110], vector quantization [13,56,68,89,98,97,101], and prediction-error [30,33,55,80,114]. A detailed review of reversible watermarking schemes is given in [46].…”

Section: Introductionmentioning

confidence: 99%

Data Hiding Schemes: A Survey

Ali¹,

Ahn²,

Pant³

2016

Gate to Computer Science and Research

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Data hiding is the process of hiding an amount of data, called secret message or watermark, into a cover media that may be audio, video, or image signal, in an imperceptible way for different purposes. Due to the advances in generation, storage, and communication technology of digital media, the necessity and importance of data hiding has drawn the attention of many researchers all over the world resulting in a lot of variants of data hiding scheme. This chapter provides a detailed review of the basic concepts of data hiding and a survey of its major variants developed so far. The chapter classifies the data hiding schemes based on several aspects of data hiding comprising artificial intelligence. Furthermore, the chapter also provides the recommendations to the interested users for further research. This review may be a useful insight and a good source for the users who are interested in the application of artificial intelligence in data hiding.

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“…In the literature, the data hiding techniques can be classified into two categories: irreversible data hiding techniques [1]- [2] and reversible data hiding techniques [3]- [10]. In the reversible data hiding technique, the secret data can be extracted and the original host images can be recovered simultaneously.…”

Section: Introductionmentioning

confidence: 99%

“…Basically, two main approaches of the reversible data hiding techniques had been introduced. They are the difference expansion (DE) approach [6] and the histogram shifting (HS) approach [7]- [10]. Some reversible data hiding techniques that use the mix of these two approaches had also been designed.…”

Section: Introductionmentioning

confidence: 99%

Residual Histogram Shifting Technique Based on Cascading Prediction for Reversible Data Hiding

Tsai

Yeh

et al. 2015

Lecture Notes in Electrical Engineering

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Abstract.To reversibly embed the secret data into the host image, the histogram shifting (HS) technique was proposed by embedding 1-bit secret data into the pixels in the peak points. To improve the hiding capacity of the histogram shifting technique, the residual histogram shifting (RHS) technique had been proposed. The prediction errors in the peak points of the residual histogram are used to embed the secret data. To further improve the hiding capacity, an improved block-based residual histogram shifting technique is proposed in this paper. The cascading prediction mechanism is employed in the proposed technique to generate the prediction errors for each image block. Experimental results reveal that the proposed technique provides higher hiding capacity than HS and RHS while keeping good image qualities of the embedded images.

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High capacity reversible data hiding scheme based on residual histogram shifting for block truncation coding

Cited by 48 publications

References 25 publications

Enhancing the Performance of the Data Embedment Process through Encoding Errors

Enhancing the Performance of the Data Embedment Process through Encoding Errors

Data Hiding Schemes: A Survey

Residual Histogram Shifting Technique Based on Cascading Prediction for Reversible Data Hiding

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