High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images
Unlike histogram-based reversible data hiding (RDH), the general distortion-based framework considers pixel-by-pixel distortions, which is a new research direction in RDH. The advantage of the general distortion-based RDH method is that it can enhance the visual quality of the marked image by embedd...
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MDPI AG
2023-09-01
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Series: | Mathematics |
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Online Access: | https://www.mdpi.com/2227-7390/11/19/4111 |
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author | Xiang Li Xiaolong Li Mengyao Xiao Yao Zhao Hsunfang Cho |
author_facet | Xiang Li Xiaolong Li Mengyao Xiao Yao Zhao Hsunfang Cho |
author_sort | Xiang Li |
collection | DOAJ |
description | Unlike histogram-based reversible data hiding (RDH), the general distortion-based framework considers pixel-by-pixel distortions, which is a new research direction in RDH. The advantage of the general distortion-based RDH method is that it can enhance the visual quality of the marked image by embedding data into visually insensitive regions (e.g., edges and textures). In this paper, following this direction, a high-capacity RDH approach based on multi-embedding is proposed. The cover image is decoupled to select the embedding sequence that can better utilize texture pixels and reduce the size of the reconstruction information, and a multi-embedding strategy is proposed to embed the secret data along with the reconstruction information by matrix embedding. The experimental results demonstrate that the proposed method provides a superior visual quality and higher embedding capacity than some state-of-the-art RDH works for binary images. With an embedding capacity of 1000 bits, the proposed method achieves an average PSNR of 49.45 dB and an average SSIM of 0.9705 on the test images. This marks an improvement of 1.1 dB in PSNR and 0.0242 in SSIM compared to the latest state-of-the-art RDH method. |
first_indexed | 2024-03-10T21:39:53Z |
format | Article |
id | doaj.art-8155b9be9aaa45aead090088b44bb98a |
institution | Directory Open Access Journal |
issn | 2227-7390 |
language | English |
last_indexed | 2024-03-10T21:39:53Z |
publishDate | 2023-09-01 |
publisher | MDPI AG |
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series | Mathematics |
spelling | doaj.art-8155b9be9aaa45aead090088b44bb98a2023-11-19T14:43:30ZengMDPI AGMathematics2227-73902023-09-011119411110.3390/math11194111High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary ImagesXiang Li0Xiaolong Li1Mengyao Xiao2Yao Zhao3Hsunfang Cho4Institute of Information Science, Beijing Jiaotong University, Beijing 100044, ChinaInstitute of Information Science, Beijing Jiaotong University, Beijing 100044, ChinaInstitute of Information Science, Beijing Jiaotong University, Beijing 100044, ChinaInstitute of Information Science, Beijing Jiaotong University, Beijing 100044, ChinaShanghai Data Exchange Corporation, Shanghai 201203, ChinaUnlike histogram-based reversible data hiding (RDH), the general distortion-based framework considers pixel-by-pixel distortions, which is a new research direction in RDH. The advantage of the general distortion-based RDH method is that it can enhance the visual quality of the marked image by embedding data into visually insensitive regions (e.g., edges and textures). In this paper, following this direction, a high-capacity RDH approach based on multi-embedding is proposed. The cover image is decoupled to select the embedding sequence that can better utilize texture pixels and reduce the size of the reconstruction information, and a multi-embedding strategy is proposed to embed the secret data along with the reconstruction information by matrix embedding. The experimental results demonstrate that the proposed method provides a superior visual quality and higher embedding capacity than some state-of-the-art RDH works for binary images. With an embedding capacity of 1000 bits, the proposed method achieves an average PSNR of 49.45 dB and an average SSIM of 0.9705 on the test images. This marks an improvement of 1.1 dB in PSNR and 0.0242 in SSIM compared to the latest state-of-the-art RDH method.https://www.mdpi.com/2227-7390/11/19/4111reversible data hidinggeneral distortion modelmulti-embeddingbinary images |
spellingShingle | Xiang Li Xiaolong Li Mengyao Xiao Yao Zhao Hsunfang Cho High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images Mathematics reversible data hiding general distortion model multi-embedding binary images |
title | High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images |
title_full | High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images |
title_fullStr | High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images |
title_full_unstemmed | High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images |
title_short | High-Quality Reversible Data Hiding Based on Multi-Embedding for Binary Images |
title_sort | high quality reversible data hiding based on multi embedding for binary images |
topic | reversible data hiding general distortion model multi-embedding binary images |
url | https://www.mdpi.com/2227-7390/11/19/4111 |
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