Compressive Sensing Image Steganography via Directional Lifting Wavelet Transform

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Abstract

This paper proposes a deep-based compressive sensing (CS) image steganography scheme that inserts the plain image into the directional lifting wavelet transform (DLWT) domain of the carrier image. For the data hiding processing, we exploit two logistic maps to create the measurement matrix and simulated noise respectively, which are used to randomly under-sample and diffuse the plain image to obtain the secret image. Then, we employ singular value decomposition (SVD) to embed the secret image into the DLWT domain of the carrier image, which generates the meaningful stego image. For the data extraction, we introduce the deep-based CS reconstruction algorithm to enhance the quality of the reconstructed image. Experimental results show that the proposed approach maintains security while achieving a high quality of the stego image and the reconstructed image.

Original languageEnglish
Title of host publicationInformation and Communications Security - 23rd International Conference, ICICS 2021, Proceedings
EditorsDebin Gao, Qi Li, Xiaohong Guan, Xiaofeng Liao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages93-109
Number of pages17
ISBN (Print)9783030880514
DOIs
StatePublished - 2021
Event23rd International Conference on Information and Communications Security, ICICS 2021 - Chongqing, China
Duration: 19 Nov 202121 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12919 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Information and Communications Security, ICICS 2021
Country/TerritoryChina
CityChongqing
Period19/11/2121/11/21

Keywords

  • Compressive sensing
  • DLWT
  • Image steganography

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