scholarly journals Reversible Data Hiding Scheme Using Adaptive Block Truncation Coding Based on an Edge-Based Quantization Approach

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 765 ◽  
Author(s):  
Chia-Chen Lin ◽  
Ching-Chun Chang ◽  
Zhi-Ming Wang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Zero Point ◽  
Edge Image ◽  
Block Truncation Coding ◽  
Canny Edge ◽  
High Embedding Capacity ◽  
Processing Block ◽  
And Performance ◽  
Edge Based

In this paper, we provide a novel reversible data hiding method using adaptive block truncation coding based on an edge-based quantization (ABTC-EQ) approach. We exploit the characteristic not being used in ABTC-EQ. To accomplish this, we first utilized a Canny edge detector to obtain an edge image and classify each block in a cover image into two versions, edge-block and non-edge-block. Subsequently, k-means clustering was used to obtain three quantization levels and derive the corresponding bit map while the current processing block was the case of an edge-block. Then Zero-Point Fixed Histogram Shifting (ZPF-HS) was applied to embed the secret information into compressed code. The experimental results show that our method provides a high embedding capacity for each test image and performance is better than other methods.

scholarly journals Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

2021 ◽  
Vol 11 (15) ◽  
pp. 6741
Author(s):  
Chia-Chen Lin ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Wen-Chi Chang
Keyword(s):  
Data Hiding ◽  
Free Space ◽  
Reversible Data Hiding ◽  
Secret Message ◽  
Embedding Capacity ◽  
Absolute Moment ◽  
Compressed Images ◽  
High Embedding Capacity ◽  
Significant Attention ◽  
Efficiency Rate

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

scholarly journals A novel two-dimensional reversible data hiding method with high embedding capacity in H.264/advanced video coding

2020 ◽  
Vol 16 (3) ◽  
pp. 155014772091100
Author(s):  
Yi Chen ◽  
Hongxia Wang ◽  
Xiaoxu Tang ◽  
Yong Liu ◽  
Hanzhou Wu ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Error Concealment ◽  
Similarity Index ◽  
Two Dimensional ◽  
Embedding Capacity ◽  
High Embedding Capacity ◽  
Advanced Video Coding

Developing the technology of reversible data hiding based on video compression standard, such as H.264/advanced video coding, has attracted increasing attention from researchers. Because it can be applied in some applications, such as error concealment and privacy protection. This has motivated us to propose a novel two-dimensional reversible data hiding method with high embedding capacity in this article. In this method, all selected quantized discrete cosine transform coefficients are first paired two by two. And then, each zero coefficient-pair can embed 3 information bits and the coefficient-pairs only containing one zero coefficient can embed 1 information bit. In addition, only one coefficient of each one of the rest coefficient-pairs needs to be changed for reversibility. Therefore, the proposed two-dimensional reversible data hiding method can obtain high embedding capacity when compared with the related work. Moreover, the proposed method leads to less degradation in terms of peak-signal-to-noise ratio, structural similarity index, and less impact on bit-rate increase.

A High Capacity Reversible Data Hiding Scheme Based on Multi-Level Integer DWT and Histogram Modification

2014 ◽  
Vol 6 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Shun Zhang ◽  
Tie-gang Gao ◽  
Fu-sheng Yang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Wavelet Transformation ◽  
High Capacity ◽  
Discrete Wavelet ◽  
Embedding Capacity ◽  
Discrete Cosine Transformation ◽  
Histogram Modification ◽  
Multi Level ◽  
High Embedding Capacity

A reversible data hiding scheme based on integer DWT and histogram modification is proposed. In the scheme, the cover media is firstly transformed by Integer DWT (Discrete Wavelet Transformation); then information is embedded through the modification of histograms of the middle and high frequency sub-bands of the DWT coefficients. In order to increase the embedding capacity, a multi-level scheme is proposed, which achieved both high embedding capacity and reversibility. Extensive experimental results have shown that the proposed scheme achieves both higher embedding capacity and lower distortion than spatial domain histogram modification based schemes; and it achieved better performance than integer DCT (Discrete Cosine Transformation) based histogram modification scheme.

scholarly journals Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Chunqiang Yu ◽  
Xianquan Zhang ◽  
Zhenjun Tang ◽  
Yan Chen ◽  
Jingyu Huang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Visual Quality ◽  
Input Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Encrypted Image ◽  
High Embedding Capacity ◽  
Additive Homomorphism

Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

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