Adaptive reversible data hiding algorithm for interpolated images using sorting and coding

算术下溢 直方图 像素 信息隐藏 算法 峰值信噪比 隐写分析技术 计算机科学 分类 人工智能 隐写术 编码(社会科学) 数学 模式识别(心理学) 图像(数学) 统计 程序设计语言
作者
Xiangguang Xiong,Yi Chen,Mengting Fan,Siyao Zhong
出处
期刊:Journal of information security and applications [Elsevier]
卷期号:66: 103137-103137 被引量:10
标识
DOI:10.1016/j.jisa.2022.103137
摘要

Existing reversible data hiding (RDH) algorithms based on the interpolation technology (IT) have high embedding capacities and visual qualities. However, they usually embed secret data directly into interpolated pixels sequentially, resulting in that the visual qualities may not be optimal. To address this problem, an adaptive IT-based RDH algorithm is proposed. First, for a given interpolated image, the amount of data that can be embedded into each interpolated pixel is sorted in the ascending order. Next, the secret data to be embedded are recoded and sequentially embedded into interpolated pixels after overflow/underflow preprocessing based on the obtained index. The experimental results demonstrate that the proposed algorithm outperforms several state-of-the-art RDH algorithms based on IT. On average, the average peak signal-to-noise ratio (PSNR) of our algorithm is improved by approximately 25%. In comparison with traditional RDH algorithms using histogram shifting and pixel value ordering, our algorithm also achieves a higher PSNR. In addition, our algorithm can resist histogram and regular singular steganalysis attacks. These results clearly demonstrate that the proposed algorithm is effective.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
景平完成签到,获得积分10
1秒前
ri_290发布了新的文献求助10
1秒前
2秒前
2秒前
赘婿应助咩咩咩采纳,获得30
3秒前
王w应助诚心文博采纳,获得30
3秒前
4秒前
龙卷风摧毁停车场完成签到,获得积分10
4秒前
一指墨发布了新的文献求助10
5秒前
科目三应助唐俊杰采纳,获得10
5秒前
cc应助方方方方方采纳,获得50
5秒前
夏沫完成签到,获得积分10
5秒前
6秒前
sherry发布了新的文献求助10
7秒前
7秒前
8秒前
8秒前
乐乐应助yunshui采纳,获得10
8秒前
HSY完成签到,获得积分10
8秒前
wanci应助BeautyZ采纳,获得10
9秒前
10秒前
10秒前
CodeCraft应助WeiPaiHWuFXZ采纳,获得10
10秒前
赘婿应助含蓄的大米采纳,获得10
10秒前
11秒前
11秒前
12秒前
田様应助张晓年采纳,获得10
12秒前
12秒前
一指墨完成签到,获得积分10
13秒前
爆米花应助ddd采纳,获得10
13秒前
13秒前
海纳百川完成签到,获得积分10
13秒前
量子星尘发布了新的文献求助10
13秒前
冬易发布了新的文献求助10
13秒前
欣喜冷卉完成签到,获得积分20
14秒前
peng完成签到,获得积分10
14秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2025-2031全球及中国金刚石触媒粉行业研究及十五五规划分析报告 9000
Encyclopedia of the Human Brain Second Edition 8000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Real World Research, 5th Edition 680
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5684488
求助须知:如何正确求助?哪些是违规求助? 5036727
关于积分的说明 15184287
捐赠科研通 4843754
什么是DOI,文献DOI怎么找? 2596869
邀请新用户注册赠送积分活动 1549511
关于科研通互助平台的介绍 1508027