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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106870


    Title: Image reversibility in data embedding on the basis of blocking-predictions
    Authors: 許富皓;Hsu, Fu-Hau;Wu, Min-Hao;Yang, Cheng-Hsing;Wang, Shiuh-Jeng
    Contributors: 資訊電機學院資訊工程學系
    Keywords: Blocking;Communications Engineering;Computer architecture;Computer Communication Networks;Data imaging;Distortion;Engineering;Image quality;Information Systems and Communication Service;Multilevel;Networks;Noise levels;Peer to peer computing;Preserves;Signal,Image and Speech Processing;Texts
    Date: 2014-01-01
    Issue Date: 2026-04-23 13:47:12 (UTC+8)
    Publisher: Springer New York;Boston: Springer US
    Abstract: 摘要: The popularity of peer-to-peer (P2P) multimedia file sharing applications such as voice, files, images, video, texts have created a flurry of recent research activity into P2P architectures. Reversible data hiding has drawn considerable attention in recent years. Being reversible, the decoder can extract the hidden data and recover the cover image completely. In this paper we used the block prediction to achieve histogram-based reversible data hiding. The histogram is created by exploiting all difference values between pixels and their predictive values. Experimental results show that our scheme is capable of providing great embedding capacity without making noticeable distortion. In the one-level data hiding, our scheme preserves image quality larger than 48 dB and has the best capacity. Moreover, in the multilevel cases, our scheme performs better than other existing schemes. Our scheme can successfully increase the embedding capacity from histogram-based data hiding and preserve image quality well.
    其他題名: Peer-to-Peer Netw. Appl
    出版者: Boston: Springer US
    出版日期: 2014-12-01
    出處: Peer-to-peer networking and applications, 2014-12, Vol.7 (4), p.723-736
    版權: Springer Science+Business Media New York 2013
    版權: Springer Science+Business Media New York 2014
    識別號: ISSN: 1936-6442
    識別號: EISSN: 1936-6450
    識別號: DOI: 10.1007/s12083-013-0212-8
    Appears in Collections:[Department of Computer Science and information Engineering] journal & Dissertation

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