Research on multiple-image encryption mechanism based on Radon transform and ghost imaging

加密 氡变换 计算机科学 稳健性(进化) 笛卡尔坐标系 多路复用 计算机视觉 传输(电信) 算法 人工智能
作者
Leihong Zhang,Wang Yang,Dawei Zhang
出处
期刊:Optics Communications [Elsevier]
卷期号:504: 127494-127494 被引量:3
标识
DOI:10.1016/j.optcom.2021.127494
摘要

In the process of multiple-image encryption, there are some problems such as low reconstruction accuracy, easy cross-talk, and poor robust performance. To solve these problems, a multiple-image encryption algorithm based on Radon transform and ghost imaging is proposed. Radon transform is applied to the encryption system of ghost imaging. The Cartesian coordinates of the two-dimensional images are firstly converted to the polar coordinates. Then, the Radon transform is fully used to obtain the projection of digital images at arbitrarily given angles. By adjusting the projecting angle interval, the spatial division multiplexing is used to realize the multiple-image encryption. By the numerical simulations and optical experiments, the feasibility of the proposed encryption system is verified. The results show that the proposed system not only reduces the amount of data transmission, but also improves the precision of the reconstructed image and the robustness of the encryption system. • The use of Radon transform reduces the data transmission and improves the imaging quality. • Radon transform is applied to the encryption system of ghost imaging (GI), which improves the robustness of the system. • The use of spatial division multiplexing can realize the encryption of multiple-image and eliminate cross-talk effect.
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
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
sak完成签到,获得积分10
1秒前
Shuo Yang发布了新的文献求助20
1秒前
呜呜呜呜发布了新的文献求助10
1秒前
在水一方应助hhzz采纳,获得10
1秒前
旧是完成签到 ,获得积分10
2秒前
脑洞疼应助科研通管家采纳,获得10
2秒前
杨小胖完成签到 ,获得积分10
3秒前
CodeCraft应助科研通管家采纳,获得10
3秒前
mm发布了新的文献求助10
3秒前
3秒前
bkagyin应助科研通管家采纳,获得10
3秒前
shouyu29应助科研通管家采纳,获得10
3秒前
天天快乐应助科研通管家采纳,获得10
3秒前
RC_Wang应助科研通管家采纳,获得10
3秒前
充电宝应助科研通管家采纳,获得10
3秒前
3秒前
领导范儿应助科研通管家采纳,获得10
3秒前
科研通AI5应助科研通管家采纳,获得10
3秒前
田様应助科研通管家采纳,获得10
3秒前
4秒前
丘比特应助科研通管家采纳,获得10
4秒前
CodeCraft应助科研通管家采纳,获得30
4秒前
sutharsons应助科研通管家采纳,获得30
4秒前
归海含烟完成签到,获得积分10
4秒前
科研通AI2S应助科研通管家采纳,获得10
4秒前
shire应助科研通管家采纳,获得10
4秒前
Orange应助科研通管家采纳,获得10
4秒前
思源应助科研通管家采纳,获得10
4秒前
RC_Wang应助科研通管家采纳,获得10
4秒前
研友_VZG7GZ应助科研通管家采纳,获得10
4秒前
充电宝应助科研通管家采纳,获得10
5秒前
顾矜应助科研通管家采纳,获得10
5秒前
大个应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
匹诺曹发布了新的文献求助10
5秒前
唐画完成签到 ,获得积分10
5秒前
5秒前
5秒前
淡淡采白关注了科研通微信公众号
6秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 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 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808