scholarly journals High Capacity Data Hiding in Encrypted Image Based on Compressive Sensing for Nonequivalent Resources

2019 ◽  
Vol 58 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Di Xiao ◽  
Jia Liang ◽  
Qingqing Ma ◽  
Yanping Xiang ◽  
Yushu Zhang
Keyword(s):  
Compressive Sensing ◽  
Data Hiding ◽  
High Capacity ◽  
Encrypted Image ◽  
Capacity Data

High-capacity separable data hiding in encrypted image based on compressive sensing

2015 ◽  
Vol 75 (21) ◽  
pp. 13779-13789 ◽  
Author(s):  
Di Xiao ◽  
Hongkun Cai ◽  
Yong Wang ◽  
Sen Bai
Keyword(s):  
Compressive Sensing ◽  
Data Hiding ◽  
High Capacity ◽  
Encrypted Image

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

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.

scholarly journals High-Capacity Reversible Data Hiding in Encrypted Images by Information Preprocessing

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xi-Yan Li ◽  
Xia-Bing Zhou ◽  
Qing-Lei Zhou ◽  
Shi-Jing Han ◽  
Zheng Liu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Main Idea ◽  
Original Image ◽  
Chaos Encryption ◽  
Secret Information ◽  
Encrypted Image ◽  
Encrypted Images ◽  
Scanned Documents

With the development of cloud computing, high-capacity reversible data hiding in an encrypted image (RDHEI) has attracted increasing attention. The main idea of RDHEI is that an image owner encrypts a cover image, and then a data hider embeds secret information in the encrypted image. With the information hiding key, a receiver can extract the embedded data from the hidden image; with the encryption key, the receiver reconstructs the original image. In this paper, we can embed data in the form of random bits or scanned documents. The proposed method takes full advantage of the spatial correlation in the original images to vacate the room for embedding information before image encryption. By jointly using Sudoku and Arnold chaos encryption, the encrypted images retain the vacated room. Before the data hiding phase, the secret information is preprocessed by a halftone, quadtree, and S-BOX transformation. The experimental results prove that the proposed method not only realizes high-capacity reversible data hiding in encrypted images but also reconstructs the original image completely.

scholarly journals Secure High Capacity Data Hiding for 3d Meshes

2016 ◽  
Vol 2016 (21) ◽  
pp. 1-7
Author(s):  
V. Itier ◽  
A.G. Bors ◽  
W. Puech ◽  
J.-P. Pedeboy
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Capacity Data

High capacity data hiding scheme based on multi-bit encoding function

Optik ◽  
2016 ◽  
Vol 127 (4) ◽  
pp. 1762-1769 ◽  
Author(s):  
Wen-Chung Kuo ◽  
Shao-Hung Kuo ◽  
Chun-Cheng Wang ◽  
Lih-Chyau Wuu
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Capacity Data
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