基于图像灰度熵分解的密文图像高载荷可逆信息隐藏

Reversible data hiding in encrypted images is an emerging technology aimed at embedding additional information into cipher-data without revealing the plaintext content and recovering the original plaintext content error-free. However, the small payload keeps it away from real applications because the information entropy of encrypted images often tend to the maximum and leave only a few redundant space for data embedding. To solve this problem, this project adopts new idea of “creating residual entropy space” instead of the traditional concept:“ using the limited residual entropy space”, and focus on the research of reversible data hiding in encrypted images with high payload based on image granulation and energy concentration by using the theory of information entropy and granular computing. The main contents are as following: 1) Side information minimization in reversible data hiding; 2) Image granulation, reversible decomposition coding, reconstruction research and statistical analysis; 3) Reversible data hiding in encrypted images based on image decomposition; 4) Reversible data hiding in encrypted compression images. The achievements of this project will be significantly meaningful for research and application of reversible data hiding in encrypted domain. Furthermore, this project will provide new ideas, methods and new technologies to solve the problems in the former social development such as the privacy and security management of massive image data. The achievements of this project are of great significance to national security and privacy protection.

密文图像可逆信息隐藏在图像加密后嵌入附加信息，同时又可无损恢复图像明文，是图像信息隐藏领域新兴研究热点。当前制约该技术发展的瓶颈之一是有效载荷低。针对该问题，本项目以信息论为指导，突破传统的“利用有限剩余熵空间”的概念，提出“创造剩余熵空间”的思路，借鉴粒化计算方法论从熵的角度对图像进行粒化分解和能量集中加密，从最小化辅助信息量和降低载体数据信息熵两方面着手，研究具有高载荷的密文图像可逆信息隐藏方案，包括可逆信息隐藏中的辅助信息最小化研究；基于灰度熵的图像粒化、无损分解编码、重构机制及统计分析研究；基于图像灰度熵分解的密文域可逆信息隐藏研究；压缩图像中的密文域可逆信息隐藏研究。将为密文域可逆信息隐藏的发展提供新的研究思路，并拓展其应用领域，其成果既能为解决当前社会发展中对海量图像数据进行隐私保护和安全管理的问题提供新思路、新方法、新技术，又对国家安全和隐私保护具有重要意义。