网络与信息安全学报2026，Vol.12Issue(4)：33-49,17.DOI:10.11959/j.issn.2096-109x.AQ26098
基于组合预测优化和分层块压缩的加密图像可逆数据隐藏
Reversible data hiding in encrypted images based on combined prediction optimization and hierarchical block compression
摘要
Abstract
Reversible data hiding in encrypted images(RDHEI),which can simultaneously protect the cover image and private data,has been widely studied in recent years.To address the issues of limited embedding capacity due to underutilization of high bit-planes redundancy and inaccurate prediction of complex image regions,a novel RDHEI method based on combined prediction optimization,hierarchical block compression,and context-based adaptive binary arithmetic coding(CABAC)was proposed.Firstly,by integrating the combined predictor and pre-diction error modification(PEM)strategy,the accuracy of prediction in complex regions and compression effi-ciency were effectively improved.Secondly,a quadtree-based adaptive hierarchical block compression strategy was designed to replace fixed partitioning,allowing for more flexible redundancy minimization.Finally,CABAC was applied to further reduce auxiliary information.This approach effectively increases embedding capacity and en-sures lossless image recovery.Experimental results show that the proposed method outperforms existing main-stream methods in terms of embedding rate.On the three public datasets BOSSbase,BOWS-2 and UCID,the aver-age embedding rates of the proposed method are 4.324 5 bit/pixel,4.232 7 bit/pixel and 3.575 2 bit/pixel,respec-tively,which correspond to improvements of 3.63%,3.59%and 2.38%over existing mainstream methods.关键词
可逆数据隐藏/加密图像/组合预测优化/分层块压缩Key words
reversible data hiding/encrypted images/combined prediction optimization/hierarchical block com-pression分类
信息技术与安全科学引用本文复制引用
任方,王静,张星,杨腾飞..基于组合预测优化和分层块压缩的加密图像可逆数据隐藏[J].网络与信息安全学报,2026,12(4):33-49,17.基金项目
国家自然科学基金资助项目(No.62272386) （No.62272386）
陕西省自然科学基金资助项目(No.2024JC-YBMS-524) （No.2024JC-YBMS-524）
西安邮电大学研究生创新基金资助项目(No.CXJJZL2025036,No.CXJJZL2025034)The National Natural Science Foundation of China(No.62272386),The Natural Science Foundation of Shaanxi Province(No.2024JC-YBMS-524),The Postgraduate Innovation Fund of Xi'an University of Posts and Telecommuni-cations(No.CXJJZL2025036,No.CXJJZL2025034) （No.CXJJZL2025036,No.CXJJZL2025034）
