Reversible Data Hiding in Encrypted Images Based on Time-Varying Huffman Coding Table

Yang, Yaolin; He, Hongjie; Chen, Fan; Yuan, Yuan; Mao, Ningxiong

doi:10.1109/tmm.2023.3238549

Cited by 10 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compared with Qiu et al's method [44], the proposed method can achieve a gain of 0.007, 0.032, 0.090, 0.098 and 0.015 bpp over Qiu et al's method [44] for the five images. As for Yang et al's method [45], our gains are 0.051, 0.066, 0.137, 0.065 and 0.053 bpp for the five images. &KHQDQG&KDQJ>@ <LQHWDO>@ <LQHWDO>@ <LQHWDO>@ <XHWDO>@ 4LXHWDO>@ <DQJHWDO>@ 3URSRVHG Fig.…”

Section: Comparison With Sota Methodssupporting

confidence: 53%

“…Compared with [44], our gains are 0.080, 0.115 and 0.121 bpp for BOSS-Base, BOWS-2 and UCID datasets, respectively. The above results demonstrate that the proposed method has excellent embedding performance and outperforms the existing SOTA methods [38]- [45]. Moreover, the runtime comparison is conducted.…”

Section: Comparison With Sota Methodsmentioning

confidence: 62%

“…The embedding capacity of its RRBE scheme is larger than all aforementioned methods. Yang et al [45] adopted the dynamic Huffman coding with a timestamp to encode the prediction errors, which achieves good performance on embedding capacity as well as improves the security of RDHEI. In [46], the prediction errors are decomposed into nine bit-planes including a sign bit-plane.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Reversible Data Hiding in Encrypted Images with Asymmetric Coding and Bit-plane Block Compression

Zhang,

He,

et al. 2024

IEEE Trans. Multimedia

View full text Add to dashboard Cite

Reversible data hiding in encrypted images (RD-HEI) is an effective technology of protecting private data. In this paper, a high-capacity RDHEI method with asymmetric coding and bit-plane block compression is proposed. Our major contributions are twofold. (1) We propose an asymmetric coding technique for processing prediction error (PE) blocks before encryption. The proposed asymmetric coding technique does not generate the sign bit-plane and facilitates massive 0s converging on the high bit-planes. This is beneficial to reserve the embedding room. (2) We present a bit-plane block compression technique for improving the embedding capacity. This technique divides the PE codes in a block into two parts which are both compressed and thus contribute a large embedding room. Experimental results demonstrate that the average embedding rates of the proposed method are 4.156, 4.063 and 3.450 bpp on the BOSSBase, BOWS-2 and UCID datasets, respectively. Comparisons show that our average embedding rates on the three datasets are all bigger than those of some state-of-the-art methods.

show abstract

Section: Comparison With Sota Methodssupporting

confidence: 53%

Section: Comparison With Sota Methodsmentioning

confidence: 62%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Reversible Data Hiding in Encrypted Images with Asymmetric Coding and Bit-plane Block Compression

Zhang,

He,

et al. 2024

IEEE Trans. Multimedia

View full text Add to dashboard Cite

show abstract

“…Before going to the performance and security analysis of the proposed algorithm, we first explain the Quality assessment metrics used for critical analysis of the proposed algorithm shown in Table 3 55 – 57 .…”

Section: Resultsmentioning

confidence: 99%

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

Rahman,

Uddin,

Hussain

et al. 2023

Sci Rep

View full text Add to dashboard Cite

In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection.

show abstract

“…So far, scholars have proposed many RDH methods, and these algorithms can be broadly categorized into lossless compression (LC) [8][9][10], , difference expansion (DE) [11][12][13], histogram shifting (HS) [14][15][16] and prediction error expansion (PEE) [17][18][19][20][21]. Although these methods are designed from different perspectives, there are only two ultimate goals: to increase the embedding capacity and to reduce the distortion.…”

Section: Introductionmentioning

confidence: 99%

Reversible Data Hiding for Recursion-PVO Based on Pixels Selection

Ge,

Shen,

Xia

et al. 2024

Preprint

View full text Add to dashboard Cite

Pixel value ordering (PVO) is one of the most commonly used methods in reversible data hiding (RDH). Most PVO methods currently chunk images, categorize them according to the space complexity of the chunks, and adopt different embedding strategies for different chunk categories. Although this approach achieves some results, the utilization of pixel redundancy is still insufficient. In order to expand the embedding capacity of RDH and improve the embedding performance, a high-fidelity reversible data hiding method based on pixels selection and recursion-PVO is proposed in this paper. Specially, for uniformly divided non-overlapping blocks, the set of pixels with the smallest and second-smallest variance values within each block is selected to form a new block to be embedded, thus further utilizing pixel redundancy. Then, the embedding capacity is improved by transforming some reference pixels into to-be-embedded pixels and forming pixel pairs with other reference pixels to calculate the prediction error. Experimental results show that the proposed method has better performance compared to some state-of-the-art methods. In particular, for the commonly used test image Lena, the PSNR after embedding 10,000 bits of data is up to 63.13 dB.

show abstract

Reversible Data Hiding in Encrypted Images Based on Time-Varying Huffman Coding Table

Cited by 10 publications

References 39 publications

Reversible Data Hiding in Encrypted Images with Asymmetric Coding and Bit-plane Block Compression

Reversible Data Hiding in Encrypted Images with Asymmetric Coding and Bit-plane Block Compression

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

Reversible Data Hiding for Recursion-PVO Based on Pixels Selection

Contact Info

Product

Resources

About