Reversible Data Hiding of Subsampled Model for Edge-Information Prediction
This paper tries to analyze a new framework of lossless information hiding research. Its key is how to get adaptively better difference image architectures for given applications. A unique sampled pattern is introduced and described in term of high-similar interpolation image. Seeking the higher peak value in the difference-image is also our concerns. As a whole algorithm, histogram-differenceexpanded based structures are reported. Simulations results demonstrate and verify that our new approach is much effective than the nearest difference expansion method with good generalization performance.
Subsampled pattern lossless data hiding edgesensing overflow underflow
Guorui Feng Lingyan Fan
School of Communication and Information Engineering Shanghai University, Shanghai, China, 200072 Department Hangzhou Dianzi University, Hangzhou, China, 310018
国际会议
南京
英文
676-680
2010-11-01（万方平台首次上网日期，不代表论文的发表时间）