Reversible data hiding using least square predictor via the LASSO
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hwang, Hee Joon | - |
dc.contributor.author | Kim, SungHwan | - |
dc.contributor.author | Kim, Hyoung Joong | - |
dc.date.accessioned | 2021-12-21T21:40:20Z | - |
dc.date.available | 2021-12-21T21:40:20Z | - |
dc.date.created | 2021-08-30 | - |
dc.date.issued | 2016-12-07 | - |
dc.identifier.issn | 1687-5176 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/132450 | - |
dc.description.abstract | Reversible watermarking is a kind of digital watermarking which is able to recover the original image exactly as well as extracting hidden message. Many algorithms have aimed at lower image distortion in higher embedding capacity. In the reversible data hiding, the role of efficient predictors is crucial. Recently, adaptive predictors using least square approach have been proposed to overcome the limitation of the fixed predictors. This paper proposes a novel reversible data hiding algorithm using least square predictor via least absolute shrinkage and selection operator (LASSO). This predictor is dynamic in nature rather than fixed. Experimental results show that the proposed method outperforms the previous methods including some algorithms which are based on the least square predictors. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER INTERNATIONAL PUBLISHING AG | - |
dc.subject | DIFFERENCE EXPANSION | - |
dc.subject | IMAGE WATERMARKING | - |
dc.subject | COMPRESSION | - |
dc.subject | ALGORITHM | - |
dc.subject | SELECTION | - |
dc.subject | MODEL | - |
dc.title | Reversible data hiding using least square predictor via the LASSO | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Hyoung Joong | - |
dc.identifier.doi | 10.1186/s13640-016-0144-3 | - |
dc.identifier.scopusid | 2-s2.0-85002635435 | - |
dc.identifier.wosid | 000389996800001 | - |
dc.identifier.bibliographicCitation | EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING | - |
dc.relation.isPartOf | EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING | - |
dc.citation.title | EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.subject.keywordPlus | DIFFERENCE EXPANSION | - |
dc.subject.keywordPlus | IMAGE WATERMARKING | - |
dc.subject.keywordPlus | COMPRESSION | - |
dc.subject.keywordPlus | ALGORITHM | - |
dc.subject.keywordPlus | SELECTION | - |
dc.subject.keywordPlus | MODEL | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.