当前位置: X-MOL 学术Multidimens. Syst. Signal Process. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Hiding clinical information in medical images: an enhanced encrypted reversible data hiding algorithm grounded on hierarchical absolute moment block truncation coding
Multidimensional Systems and Signal Processing ( IF 1.7 ) Pub Date : 


Abstract

Reversible data hiding in the encrypted domain has attracted a lot of consideration because of the necessity for content security and protection assurance. Majority of the prior reversible data hiding algorithms are designed for absolute moment block truncation coding (AMBTC) compressed images. In this paper, an enhanced encrypted reversible data hiding algorithm grounded on hierarchical AMBTC has been proposed. In the proposed algorithm, high mean table, low mean table and bitmap sequence table obtained through hierarchical AMBTC are first encrypted using homomorphic cryptosystem and then a secret ternary data is embedded in each grey pixel of high mean table, low mean table and bitmap sequence table (except zero (0) value) without any underflow or overflow issue. Exhaustive experiments have been performed on natural and medical test images which demonstrates the superiority of the proposed algorithm over the existing reversible data hiding algorithms. Experimental study reveals that the proposed algorithm has more payload with superior image quality than the existing algorithms.



中文翻译:

在医学图像中隐藏临床信息:基于分层绝对矩块截断编码的增强型加密可逆数据隐藏算法

摘要

由于内容安全和保护保证的必要性,隐藏在加密域中的可逆数据引起了很多考虑。现有的大多数可逆数据隐藏算法都是为绝对矩块截断编码(AMBTC)压缩图像而设计的。本文提出了一种基于分层AMBTC的增强型加密可逆数据隐藏算法。在该算法中,首先使用同态密码系统对通过分层AMBTC获得的高均值表,低均值表和位图序列表进行加密,然后将秘密三进制数据嵌入高均值表,低均值表和位图序列表的每个灰色像素中(零(0)值除外)而没有任何下溢或上溢问题。已经在自然和医学测试图像上进行了详尽的实验,证明了所提出的算法优于现有的可逆数据隐藏算法。实验研究表明,与现有算法相比,该算法具有更高的有效载荷和更好的图像质量。

更新日期:2020-01-23
down
wechat
bug