Enhancing Image Watermarking With Adaptive Embedding Parameter and PSNR Guarantee

数字水印 水印 量化(信号处理) 嵌入 计算机科学 离散余弦变换 人工智能 算法 图像(数学) 稳健性(进化) 数学 生物化学 基因 化学
作者
Ying Huang,Baoning Niu,Hu Guan,Shuwu Zhang
出处
期刊:IEEE Transactions on Multimedia [Institute of Electrical and Electronics Engineers]
卷期号:21 (10): 2447-2460 被引量:104
标识
DOI:10.1109/tmm.2019.2907475
摘要

Watermarking plays an important role in identifying the copyright of an image and related issues. The state-of-the-art watermark embedding schemes, spread spectrum and quantization, suffer from host signal interference (HSI) and scaling attacks, respectively. Both of them use a fixed embedding parameter, which is difficult to take both robustness and imperceptibility into account for all images. This paper solves the problems by proposing two novel blind watermarking schemes: a spread spectrum scheme with adaptive embedding strength (SSAES) and a differential quantization scheme with adaptive quantization threshold (DQAQT). Their adaptiveness comes from the proposed adaptive embedding strategy (AEP), which maximizes the embedding strength or quantization threshold by guaranteeing the peak signal-to-noise ratio (PSNR) of the host image after embedding the watermark, and strikes the balance between robustness and imperceptibility. SSAES is HSI free by factoring in the priori knowledge about HSI. In DQAQT, an effective quantization mode is proposed to resist scaling attacks by utilizing the difference between two selected DCT coefficients with high stability. Both SSAES and DQAQT can be easily applied to other watermarking frameworks. We introduce a notion called error threshold to theoretically analyze the performance of our proposed methods in details. The experimental results consistently demonstrate that SSAES and DQAQT outperform the state-of-the-art methods in terms of imperceptibility, robustness, computational cost, and adaptability.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
上官若男应助Mila采纳,获得10
刚刚
刚刚
情怀应助ll采纳,获得10
1秒前
2秒前
3秒前
Sa完成签到,获得积分10
3秒前
小字完成签到,获得积分10
4秒前
Owen应助hu采纳,获得10
4秒前
JamesPei应助乙醇采纳,获得10
4秒前
liuderui完成签到,获得积分10
4秒前
希望天下0贩的0应助觅香采纳,获得10
5秒前
所所应助Costing采纳,获得10
5秒前
量子星尘发布了新的文献求助10
5秒前
jlb发布了新的文献求助10
5秒前
AHR发布了新的文献求助10
6秒前
在水一方应助老实的从菡采纳,获得10
7秒前
浮游应助Maoffice采纳,获得10
7秒前
wanci应助kaola采纳,获得10
8秒前
王静琳完成签到,获得积分10
8秒前
8秒前
酷波er应助梧桐断角采纳,获得10
8秒前
DU大胖完成签到,获得积分10
8秒前
善学以致用应助蓝色斑马采纳,获得10
8秒前
9秒前
Maestro_S应助文瑶琪采纳,获得10
9秒前
9秒前
小油菜完成签到,获得积分10
10秒前
段红鑫发布了新的文献求助10
10秒前
Kumiko完成签到,获得积分10
10秒前
稳重的傲芙完成签到,获得积分10
11秒前
dahong完成签到 ,获得积分10
11秒前
微解感染完成签到,获得积分10
11秒前
12秒前
鱼乐乐完成签到,获得积分10
12秒前
12秒前
QDU应助林知鲸落采纳,获得20
12秒前
12秒前
笨笨芒果完成签到,获得积分20
13秒前
CodeCraft应助小二_来篇一作采纳,获得30
13秒前
嘻哈发布了新的文献求助10
13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
Predation in the Hymenoptera: An Evolutionary Perspective 1800
List of 1,091 Public Pension Profiles by Region 1561
Binary Alloy Phase Diagrams, 2nd Edition 1200
Holistic Discourse Analysis 600
Beyond the sentence: discourse and sentential form / edited by Jessica R. Wirth 600
Red Book: 2024–2027 Report of the Committee on Infectious Diseases 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5512125
求助须知:如何正确求助?哪些是违规求助? 4606563
关于积分的说明 14500223
捐赠科研通 4541983
什么是DOI,文献DOI怎么找? 2488756
邀请新用户注册赠送积分活动 1470848
关于科研通互助平台的介绍 1443052