Content-adaptive reliable robust lossless data embedding | |
An, Lingling3; Gao, Xinbo2,3; Yuan, Yuan1![]() | |
刊名 | neurocomputing
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2012-03-01 | |
卷号 | 79页码:1-11 |
关键词 | Histogram rotation Just noticeable distortion Robust lossless data embedding |
ISSN号 | 0925-2312 |
产权排序 | 2 |
合作状况 | 国际 |
中文摘要 | it is well known that robust lossless data embedding (rlde) methods can be used to protect copyright of digital images when the intactness of host images is highly demanded and the unintentional attacks may be encountered in data communication. however, the existing rlde methods cannot be applied satisfactorily to the practical scenarios due to different drawbacks, e.g., serious "salt-and-pepper" noise, low capacity and unreliable reversibility. in this paper, we propose an effective solution to rlde by improving the histogram rotation (hr)-based embedding model. the proposed method is a content-adaptive reliable rlde or car for short. it eliminates the "salt-and-pepper" noise in hr by the pixel adjustment mechanism. therefore, reliable regions for embedding can be well constructed. furthermore, we basically expect the watermark strengths to be adaptive to different image contents, and thus we have a chance to make an effective tradeoff between invisibility and robustness. the luminance masking together with the threshold strategy is duly adopted in the proposed rlde method, so the just noticeable distortion thresholds of different local regions can be well utilized to control the watermark strengths. experimental evidence on 300 test images including natural, medical and synthetic aperture radar (sar) images demonstrates the effectiveness of the proposed data embedding method. |
英文摘要 | it is well known that robust lossless data embedding (rlde) methods can be used to protect copyright of digital images when the intactness of host images is highly demanded and the unintentional attacks may be encountered in data communication. however, the existing rlde methods cannot be applied satisfactorily to the practical scenarios due to different drawbacks, e.g., serious "salt-and-pepper" noise, low capacity and unreliable reversibility. in this paper, we propose an effective solution to rlde by improving the histogram rotation (hr)-based embedding model. the proposed method is a content-adaptive reliable rlde or car for short. it eliminates the "salt-and-pepper" noise in hr by the pixel adjustment mechanism. therefore, reliable regions for embedding can be well constructed. furthermore, we basically expect the watermark strengths to be adaptive to different image contents, and thus we have a chance to make an effective tradeoff between invisibility and robustness. the luminance masking together with the threshold strategy is duly adopted in the proposed rlde method, so the just noticeable distortion thresholds of different local regions can be well utilized to control the watermark strengths. experimental evidence on 300 test images including natural, medical and synthetic aperture radar (sar) images demonstrates the effectiveness of the proposed data embedding method. (c) 2011 elsevier b.v. all rights reserved. |
学科主题 | computer science ; artificial intelligence |
WOS标题词 | science & technology ; technology |
类目[WOS] | computer science, artificial intelligence |
研究领域[WOS] | computer science |
关键词[WOS] | statistical quantity histogram ; digital watermarking ; image watermarking |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000300138900001 |
公开日期 | 2012-09-03 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/20246] ![]() |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China 2.Xidian Univ, Minist Educ China, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China 3.Xidian Univ, Sch Elect Engn, VIPS Lab, Xian 710071, Peoples R China 4.Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, Sydney, NSW 2007, Australia |
推荐引用方式 GB/T 7714 | An, Lingling,Gao, Xinbo,Yuan, Yuan,et al. Content-adaptive reliable robust lossless data embedding[J]. neurocomputing,2012,79:1-11. |
APA | An, Lingling,Gao, Xinbo,Yuan, Yuan,Tao, Dacheng,Deng, Cheng,&Ji, Feng.(2012).Content-adaptive reliable robust lossless data embedding.neurocomputing,79,1-11. |
MLA | An, Lingling,et al."Content-adaptive reliable robust lossless data embedding".neurocomputing 79(2012):1-11. |
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