[1]丁凯孟,朱长青,罗 文,等.基于自适应PCNN与PCA的遥感影像感知哈希认证算法[J].南京师范大学学报(自然科学版),2019,42(02):17-22.[doi:10.3969/j.issn.1001-4616.2019.02.003]
　Ding Kaimeng,Zhu Changqing,Luo Wen,et al.Perceptual Hash Algorithm Based on Adaptive PCNNand PCA for Remote Sensing Image Authentication[J].Journal of Nanjing Normal University(Natural Science Edition),2019,42(02):17-22.[doi:10.3969/j.issn.1001-4616.2019.02.003]
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基于自适应PCNN与PCA的遥感影像感知哈希认证算法()
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《南京师范大学学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第42卷
期数:
2019年02期
页码:
17-22
栏目:
·数学与计算机科学·
出版日期:
2019-06-30

文章信息/Info

Title:
Perceptual Hash Algorithm Based on Adaptive PCNNand PCA for Remote Sensing Image Authentication
文章编号:
1001-4616(2019)02-0017-06
作者:
丁凯孟1; 2; 朱长青3; 罗 文3; 刘岳明2
(1.金陵科技学院网络与通信工程学院,江苏 南京 211169)(2.中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101)(3.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023)
Author(s):
Ding Kaimeng1; 2; Zhu Changqing3; Luo Wen3; Liu Yueming2
(1.School of Networks and Tele-Communications Engineering,Jinling Institute of Technology,Nanjing 211169,China)(2.State Key Laboratory of Resource and Environment Information System,Institute of Geographic Sciencesand Natural Resources Research,CAS,Beijing 100101,China)(3.Key Laboratory of Virtual Geographic Environment of Ministry of Education,Nanjing Normal University,Nanjing 210023,China)
关键词:
遥感影像; 感知哈希; 完整性认证; 自适应PCNN; 主成分分析
Keywords:
remote sensing images; perceptual hashing; integrity authentication; adaptive PCNN; PCA
分类号:
TP391
DOI:
10.3969/j.issn.1001-4616.2019.02.003
文献标志码:
A
摘要:
针对现有遥感影像感知哈希认证算法存在的鲁棒性不足的问题,本文利用PCNN在边缘检测过程中能够抑制噪声的特点,提出一种基于自适应PCNN与PCA的遥感影像感知哈希认证算法. 首先,对遥感影像进行四边形隐形格网划分之后,根据格网单元的信息熵自适应地决定PCNN的时间衰减参数. 然后,通过PCNN提取格网单元的边缘特征,进而构造格网单元的特征矩阵. 接下来,对特征矩阵进行基于PCA和信息熵的自适应摘要化,得到的序列进行加密处理后就是该格网单元的感知哈希序列. 实验表明,该算法在保持篡改敏感性的同时,对无损压缩和LSB水印嵌入具有近乎100%的鲁棒性,对有损压缩的鲁棒性在95%以上,相比于现有算法有了较大提高.
Abstract:
Due to the disadvantage of the existing perceptual hash algorithm for remote sensing image has,a perceptual hash algorithm based on adaptive PCNN and PCA for remote sensing image authentication is proposed making use of the characteristic PCNN can suppress noise during edge detection. Firstly,gird division is applied on the remote sensing image,and the parameter of decay time is adaptively defined based on the entropy of the grid. Secondly,the edge feature of each grid is detected by the PCNN,and the feature matrix of the grid is then constructed. Thirdly,the feature matrix is adaptively summarized based on PCA and grid entropy,the result is then encrypted to generate the perceptual hash value of the grid. The experiment results show that the robustness of the algorithm is greatly improved while it is sensitive to malicious tamper of the remote sensing image:it can keep nearly 100% robust to lossless compression and LSB watermark embedding,and can keep more than 95% robust to lossy compression.

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备注/Memo

备注/Memo:
收稿日期:2018-12-18.
基金项目:国家自然科学基金(41801303)、江苏省自然科学基金(BK200170116)、金陵科技学院基金(jit-fhxm-201604)、资源与环境信息系统国家重点实验室开放基金、江苏高校“青蓝工程”资助.
通讯联系人:丁凯孟,博士,中国科学院地理科学与资源研究所博士后,主要研究方向:地理数据安全. E-mail:dingkaimeng@foxmail.com
更新日期/Last Update: 2019-06-30