Next Article in Journal
Analysis of the Structure and Dynamics of European Flight Networks
Next Article in Special Issue
Natural Fractals as Irreversible Disorder: Entropy Approach from Cracks in the Semi Brittle-Ductile Lithosphere and Generalization
Previous Article in Journal
A Characterization of Maximally Entangled Two-Qubit States
Previous Article in Special Issue
Modeling Predictability of Traffic Counts at Signalised Intersections Using Hurst Exponent
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage

Electronic Engineering College, Heilongjiang University, Harbin 150080, China
*
Author to whom correspondence should be addressed.
Entropy 2022, 24(2), 246; https://doi.org/10.3390/e24020246
Submission received: 4 January 2022 / Revised: 4 February 2022 / Accepted: 5 February 2022 / Published: 7 February 2022
(This article belongs to the Collection Wavelets, Fractals and Information Theory)

Abstract

On the basis of ensuring the quality and concealment of steganographic images, this paper proposes a double-matrix decomposition image steganography scheme with multi-region coverage, to solve the problem of poor extraction ability of steganographic images under attack or interference. First of all, the cover image is transformed by multi-wavelet transform, and the hidden region covering multiple wavelet sub-bands is selected in the wavelet domain of the cover image to embed the secret information. After determining the hidden region, the hidden region is processed by Arnold transform, Hessenberg decomposition, and singular-value decomposition. Finally, the secret information is embedded into the cover image by embedding intensity factor. In order to ensure robustness, the hidden region selected in the wavelet domain is used as the input of Hessenberg matrix decomposition, and the robustness of the algorithm is further enhanced by Hessenberg matrix decomposition and singular-value decomposition. Experimental results show that the proposed method has excellent performance in concealment and quality of extracted secret images, and secret information is extracted from steganographic images attacked by various image processing attacks, which proves that the proposed method has good anti-attack ability under different attacks.
Keywords: image steganography; multi-wavelet transform; Arnold transform; Hessenberg decomposition; singular-value decomposition image steganography; multi-wavelet transform; Arnold transform; Hessenberg decomposition; singular-value decomposition

Share and Cite

MDPI and ACS Style

Pan, P.; Wu, Z.; Yang, C.; Zhao, B. Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage. Entropy 2022, 24, 246. https://doi.org/10.3390/e24020246

AMA Style

Pan P, Wu Z, Yang C, Zhao B. Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage. Entropy. 2022; 24(2):246. https://doi.org/10.3390/e24020246

Chicago/Turabian Style

Pan, Ping, Zeming Wu, Chen Yang, and Bing Zhao. 2022. "Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage" Entropy 24, no. 2: 246. https://doi.org/10.3390/e24020246

APA Style

Pan, P., Wu, Z., Yang, C., & Zhao, B. (2022). Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage. Entropy, 24(2), 246. https://doi.org/10.3390/e24020246

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop