A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity

With the rapid development of smartphones, cloud storage, and wireless communications, protecting the security of compressed images through data transmission on the Internet has become a critical contemporary issue. A series of data hiding methods for AMBTC compressed images has been proposed to solve this problem. However, most of these methods either change the file size of the final compressed code or exchange the order of two quantization values in some blocks. To reverse this situation, this paper proposes a data hiding method for strict AMBTC format images using a hybrid strategy: replacement, matrix encoding, and symmetric quantization value embedding for three block types i.e., smooth blocks, less complex blocks and highly complex blocks. According to the hybrid strategy, an efficient data hiding order is designed to achieve higher-fidelity. Experimental results show that our proposed method provides an excellent balance between image quality and hiding capacity and has no error blocks in the final stego-compressed code.

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Reversible Data Hiding for AMBTC Compressed Images Based on Matrix and Hamming Coding

Electronics ◽

10.3390/electronics10030281 ◽

2021 ◽

Vol 10 (3) ◽

pp. 281

Author(s):

Chia-Chen Lin ◽

Juan Lin ◽

Chin-Chen Chang

Keyword(s):

Data Hiding ◽

Mean Value ◽

Hamming Code ◽

File Size ◽

Hiding Capacity ◽

Compressed Images ◽

Matrix Embedding ◽

Previous State ◽

Disjoint Sets ◽

The Mean

In this paper, we propose a two-layer data hiding method by using the Hamming code to enhance the hiding capacity without causing significantly increasing computation complexity for AMBTC-compressed images. To achieve our objective, for the first layer, four disjoint sets using different combinations of the mean value (AVG) and the standard deviation (VAR) are derived according to the combination of secret bits and the corresponding bitmap, following Lin et al.’s method. For the second layer, these four disjoint sets are extended to eight by adding or subtracting 1, according to a matrix embedding with (7, 4) Hamming code. To maintain reversibility, we must return the irreversible block to its previous state, which is the state after the first layer of data is embedded. Then, to losslessly recover the AMBTC-compressed images after extracting the secret bits, we use continuity feature, the parity of pixels value, and the unique number of changed pixels in the same row to restore AVG and VAR. Finally, in comparison with state-of-the-art AMBTC-based schemes, it is confirmed that our proposed method provided two times the hiding capacity comparing with other six representative AMBTC-based schemes while maintaining acceptable file size of steog-images.

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A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189877 ◽

2021 ◽

pp. 1-11

Author(s):

Kusan Biswas

Keyword(s):

Data Hiding ◽

High Capacity ◽

Error Correcting Codes ◽

Human Vision ◽

Data Embedding ◽

Compressed Images ◽

Matrix Encoding ◽

Dct Coefficients ◽

Capacity Data ◽

Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

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HBF-DH: An Enhanced Payload Hybrid Data Hiding Method Based on a Hybrid Strategy and Block Features

IEEE Access ◽

10.1109/access.2019.2943505 ◽

2019 ◽

Vol 7 ◽

pp. 148439-148452 ◽

Cited By ~ 1

Author(s):

Zhan Yu ◽

Chia-Chen Lin ◽

Chin-Chen Chang ◽

Guo-Dong Su

Keyword(s):

Data Hiding ◽

Hybrid Strategy ◽

Hybrid Data

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An Efficient Data Hiding Method for AMBTC Compressed Images

10.1109/icce-tw52618.2021.9603198 ◽

2021 ◽

Author(s):

You-An Wang ◽

Ming-Chih Chiu ◽

Shih-Che Chien ◽

Feng-Chia Chang ◽

Kai-Lung Hua

Keyword(s):

Data Hiding ◽

Compressed Images ◽

Efficient Data

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An efficient data hiding method in images

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i6.pp4713-4720 ◽

2019 ◽

Vol 9 (6) ◽

pp. 4713

Author(s):

Saranya G

Keyword(s):

Data Hiding ◽

Medical Images ◽

Signal To Noise Ratio ◽

Clinical Information ◽

Contourlet Transform ◽

Compression Method ◽

Hiding Capacity ◽

Space Saving ◽

Efficient Data ◽

And Storage

<p class="Abstract">Data Hiding has a huge range of applications in the medical field for transmission. It is helpful in securing the documentation of the patients from the violator with good storage space. The medical images of different modalities like CT, MRI, and PET with the digitized clinical information can be sent to the doctors across the world for the treatment. Due to the bandwidth and storage constraints, medical images along with the clinical information must be compressed before transmission and storage. This paper gives a technique for hiding the digitized clinical information along with the DICOM images in Complex Contourlet Transform (CCT) Domain. It also analyses the compression method by using an Entropy Encoder method. Hence, this work suggests that the data hiding method based on Complex Contourlet Transform (CCT) is efficient and also it has a high hiding capacity. The improved value of Compression Ratio (CR), Space Saving (SS), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) shows that the new method satisfies the properties of the data hiding method.</p>

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Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

Applied Sciences ◽

10.3390/app11156741 ◽

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.

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Reversible Data Hiding in Encrypted Images Using Median Edge Detector and Two’s Complement

Symmetry ◽

10.3390/sym13060921 ◽

2021 ◽

Vol 13 (6) ◽

pp. 921

Author(s):

Rui Wang ◽

Guohua Wu ◽

Qiuhua Wang ◽

Lifeng Yuan ◽

Zhen Zhang ◽

...

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Personal Information ◽

Rapid Development ◽

Prediction Method ◽

Prediction Errors ◽

Edge Detector ◽

Secret Data ◽

Encrypted Images ◽

Cloud Servers

With the rapid development of cloud storage, an increasing number of users store their images in the cloud. These images contain many business secrets or personal information, such as engineering design drawings and commercial contracts. Thus, users encrypt images before they are uploaded. However, cloud servers have to hide secret data in encrypted images to enable the retrieval and verification of massive encrypted images. To ensure that both the secret data and the original images can be extracted and recovered losslessly, researchers have proposed a method that is known as reversible data hiding in encrypted images (RDHEI). In this paper, a new RDHEI method using median edge detector (MED) and two’s complement is proposed. The MED prediction method is used to generate the predicted values of the original pixels and calculate the prediction errors. The adaptive-length two’s complement is used to encode the most prediction errors. To reserve room, the two’s complement is labeled in the pixels. To record the unlabeled pixels, a label map is generated and embedded into the image. After the image has been encrypted, it can be embedded with the data. The experimental results indicate that the proposed method can reach an average embedding rate of 2.58 bpp, 3.04 bpp, and 2.94 bpp on the three datasets, i.e., UCID, BOSSbase, BOWS-2, which outperforms the previous work.

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