Details
| Original language | English |
|---|---|
| Article number | e1080 |
| Journal | PeerJ Computer Science |
| Volume | 8 |
| Publication status | Published - 28 Nov 2022 |
Abstract
Keywords
- ADMM, Image processing, LASSO, Optimization, Sparse approximation, Steganography
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
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In: PeerJ Computer Science, Vol. 8, e1080, 28.11.2022.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - SABMIS
T2 - sparse approximation based blind multi-image steganography scheme
AU - Agrawal, Rohit
AU - Ahuja, Kapil
AU - Steinbach, Marc C.
AU - Wick, Thomas
N1 - Publisher Copyright: © 2022 Agrawal et al.
PY - 2022/11/28
Y1 - 2022/11/28
N2 - Steganography is a technique of hiding secret data in some unsuspected cover media so that it is visually imperceptible. Image steganography, where the cover media is an image, is one of the most used schemes. Here, we focus on image steganography where the hidden data is also an image. Specifically, we embed grayscale secret images into a grayscale cover image, which is a challenging problem. Our goal is to develop a steganography scheme with enhanced embedding capacity while preserving the visual quality of the stego-image and ensuring that the stego-image is resistant to attacks. Our proposed scheme involves use of sparse approximation and our novel embedding rule, which helps to increase the embedding capacity and adds a layer of security. The stego-image is constructed by using the ADMM to solve the LASSO formulation of the underlying minimization problem. This method has a fast convergence, is easy to implement, and is extensively used in image processing. Finally, the secret images are extracted from the constructed stego-image using the reverse of our embedding rule. We perform extensive experiments on several standard images, and evaluate the embedding capacity, PSNR value, MSSIM index, NCC coefficient, entropy, and NAE. We obtain embedding capacities of 2bpp (bits per pixel), 4bpp, 6bpp, and 8bpp while embedding one, two, three, and four secret images, respectively. Our embedding capacities for the first three cases are higher than all the embedding capacities obtained in the literature. We are the first ones to embed four images. Further, there is very little deterioration in the quality of the stego-image as compared to its corresponding cover image. The quality of the original secret images and their corresponding extracted secret images is also almost the same. Further, due to our algorithmic design, our scheme is resistant to steganographic attacks as well.
AB - Steganography is a technique of hiding secret data in some unsuspected cover media so that it is visually imperceptible. Image steganography, where the cover media is an image, is one of the most used schemes. Here, we focus on image steganography where the hidden data is also an image. Specifically, we embed grayscale secret images into a grayscale cover image, which is a challenging problem. Our goal is to develop a steganography scheme with enhanced embedding capacity while preserving the visual quality of the stego-image and ensuring that the stego-image is resistant to attacks. Our proposed scheme involves use of sparse approximation and our novel embedding rule, which helps to increase the embedding capacity and adds a layer of security. The stego-image is constructed by using the ADMM to solve the LASSO formulation of the underlying minimization problem. This method has a fast convergence, is easy to implement, and is extensively used in image processing. Finally, the secret images are extracted from the constructed stego-image using the reverse of our embedding rule. We perform extensive experiments on several standard images, and evaluate the embedding capacity, PSNR value, MSSIM index, NCC coefficient, entropy, and NAE. We obtain embedding capacities of 2bpp (bits per pixel), 4bpp, 6bpp, and 8bpp while embedding one, two, three, and four secret images, respectively. Our embedding capacities for the first three cases are higher than all the embedding capacities obtained in the literature. We are the first ones to embed four images. Further, there is very little deterioration in the quality of the stego-image as compared to its corresponding cover image. The quality of the original secret images and their corresponding extracted secret images is also almost the same. Further, due to our algorithmic design, our scheme is resistant to steganographic attacks as well.
KW - ADMM
KW - Image processing
KW - LASSO
KW - Optimization
KW - Sparse approximation
KW - Steganography
UR - http://www.scopus.com/inward/record.url?scp=85147799896&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2110.11418
DO - 10.48550/arXiv.2110.11418
M3 - Article
VL - 8
JO - PeerJ Computer Science
JF - PeerJ Computer Science
M1 - e1080
ER -