Reversible Data Hiding in Encrypted Images Based on Adaptive Prediction and Labeling

作     者：Jiaohua Qin Zhibin He Xuyu Xiang Neal N.Xiong 

作者机构：College of Computer Science and Information TechnologyCentral South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer ScienceNortheastern State UniversityTahlequah74464OKUSA 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第73卷第11期

页      面：3613-3628页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：This work was supported in part by the Natural Science Foundation of Hunan Province(No.2020JJ4141),author X.X,http://kjt.hunan.gov.cn/ in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant(No.ZJWKT202204),author J.Q,http://zfsg.gd.gov.cn/xxfb/ywsd/index.html 

主　　题：Reversible data hiding adaptive gradient prediction huffman coding embedding capacity 

摘      要：Recently,reversible data hiding in encrypted images(RDHEI)based on pixel prediction has been a hot ***,existing schemes still employ a pixel predictor that ignores pixel changes in the diagonal direction during prediction,and the pixel labeling scheme is *** solve these problems,this paper proposes reversible data hiding in encrypted images based on adaptive prediction and ***,we design an adaptive gradient prediction(AGP),which uses eight adjacent pixels and combines four scanning methods(i.e.,horizontal,vertical,diagonal,and diagonal)for *** can adaptively adjust the weight of the linear prediction model according to the weight of the edge attribute of the pixel,which improves the prediction ability of the predictor for complex *** the same time,we adopt an adaptive huffman coding labeling scheme,which can adaptively generate huffman codes for labeling according to different images,effectively improving the scheme’s embedding performance on the *** experimental results show that the algorithm has a higher embedding *** embedding rate on the test image Jetplane is 4.2102 bpp,and the average embedding rate on the image dataset Bossbase is 3.8625 bpp.