Steganographic greedy algorithms for data hiding based on differences under SMVQ

Wei Jen Wang; Cheng Ta Huang; Shiau Rung Tsuei; Shiuh Jeng Wang

doi:10.1007/978-3-319-19321-2_46

Steganographic greedy algorithms for data hiding based on differences under SMVQ

Wei Jen Wang
, Cheng Ta Huang
, Shiau Rung Tsuei
, Shiuh Jeng Wang

研究成果: 雜誌貢獻 › 會議論文 › 同行評審

摘要

In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel algorithm named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images. While compared with Chen and Lin’s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53% more dB of PSNR of the stego-image quality and about 4.2% more bits of the embedding capacity on average.

原文	???core.languages.en_GB???
頁（從 - 到）	599-612
頁數	14
期刊	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	9023
DOIs	https://doi.org/10.1007/978-3-319-19321-2_46
出版狀態	已出版 - 2015
事件	13th International Workshop on Digital-Forensics and Watermarking , IWDW 2014 - Taipei, Taiwan 持續時間: 1 10月 2014 → 4 10月 2014

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10.1007/978-3-319-19321-2_46

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title = "Steganographic greedy algorithms for data hiding based on differences under SMVQ",

abstract = "In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel algorithm named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images. While compared with Chen and Lin{\textquoteright}s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53\% more dB of PSNR of the stego-image quality and about 4.2\% more bits of the embedding capacity on average.",

keywords = "Information hiding, Side-match vector quantization (SMVQ), Steganography",

author = "Wang, \{Wei Jen\} and Huang, \{Cheng Ta\} and Tsuei, \{Shiau Rung\} and Wang, \{Shiuh Jeng\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 13th International Workshop on Digital-Forensics and Watermarking , IWDW 2014 ; Conference date: 01-10-2014 Through 04-10-2014",

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AU - Wang, Wei Jen

AU - Huang, Cheng Ta

AU - Tsuei, Shiau Rung

AU - Wang, Shiuh Jeng

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel algorithm named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images. While compared with Chen and Lin’s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53% more dB of PSNR of the stego-image quality and about 4.2% more bits of the embedding capacity on average.

AB - In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel algorithm named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images. While compared with Chen and Lin’s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53% more dB of PSNR of the stego-image quality and about 4.2% more bits of the embedding capacity on average.

KW - Information hiding

KW - Side-match vector quantization (SMVQ)

KW - Steganography

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Y2 - 1 October 2014 through 4 October 2014

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Steganographic greedy algorithms for data hiding based on differences under SMVQ

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