摘要
光学信息安全是近年来在国际上新兴的、涉及交叉学科的信息安全技术。光学系统固有的高速并行处理能力、光波在自由空间传播的参数,如波长、衍射距离、振幅、相位等,均使得基于光学信息处理系统的加密或隐藏技术,较之传统信息安全技术,具有创新技术下的信息加工、大容量高效信息存储和多维度并行处理等优势。
近年来,在光学信息安全领域,涌现出大量针对多幅图像的光学信息安全技术,这些技术在内容分发、多用户身份认证及提高秘密信息的传输和存储效率等方面有广泛应用。针对这一热点,本论文结合光学信息安全的研究现状、重点介绍了近年来有关多图像光学信息安全技术的发展；通过研究常见的光学加密算法和隐藏技术,针对关键问题进行了系统和全面的分析,提出了基于光学信息处理技术的多图像压缩加密与隐藏的算法,主要工作可概括为以下四方面：
1)利用计算全息仿真光学扫描全息系统,实现一束激光对多幅图像的同步扫描和全息记录；利用衍射距离复用和掩码板,打乱数字全息的复振幅光强分布,以达到加密效果。在解密时,为了确保多图像解密分离的同步性和重建质量,利用Tikhonov正则化(Tikhonov Regularization)逆问题求解方法,实现解密分离。数值实验验证了该方案的可行性和鲁棒性；通过测试该算法参数的灵敏度,分析了算法的安全性；最后通过与同类算法相比证明该方法具有较好的重建效果。
2)利用压缩全息技术,首次在全息加密系统中实现对全息密文数据的压缩。首先,通过对光学扫描全息系统的系统函数分析,论证了该函数具有傅里叶变换特性；再次,鉴于自然图像在小波变换域内的稀疏性,且小波稀疏基与傅里叶基是不相干的,满足约束等距性,利用在多图像加密过程中的傅里叶非均匀采样,完成多图像压缩加密。最后,在逆问题求解模型中引入对图像小波基下的稀疏性约束,完成多图像的同步解密重建。
3)利用全变分(Total Variation)求解方法和小波预处理,实现对多个自然图像的压缩加密。首先,在已有的基于压缩全息的加密方案中,通过优化求解模型,以约束细节信息的全变分项代替约束光滑性的l2范数,实现了对两张自然图像的压缩加密；接着,为了减少激光在对多幅图像并行扫描时引入的串扰问题,借助小波预处理,对各个秘密图像的基本信息错位排放,完成了对多幅自然图像的压缩加密；最后,针对韩国世宗大学光电实验室的物理光学扫描全息设备生成的全息数据,实现了对真实数据的压缩加密。实验部分验证了该方案的可行性,分析了其压缩性能、重建质量及算法的安全性。
4)基于相位恢复算法,提出以较少透镜完成对多幅图像的信息隐藏。首先,通过相位滤波器,实现对多幅待隐藏图像的频移复用,输出一张包含所有待隐藏图像频域信息的图；接着,利用相位恢复算法,寻找特定的相位板,使得待隐藏图像经过调制后趋近于载体图像；最后将含有秘密信息的载体,放置在正确的位置,应用相位板和相位滤波器即可还原对应的秘密图像。数值实验验证了该算法的可行性,分析了其迭代收敛性、不可感知性、鲁棒性及压缩性能。
Optical information security is becoming a state-of-the-art cross-discipline topic nowadays. An optical system is characterized by the powerful capability of information processing parallely across three dimensions and advantageous at providing multiple parameters regulating a propagation, such as a wavelength, diffraction distance, amplitude and phase. These advantages guarantee the information encryption and hiding by optical processing to perform at multiple dimensions with a mass-storage, and parallel information processing, apparently over conventional information security techniques. Recently, a great number of optical information security techniques for multiple images mushroom, which results in the fact that these techniques can be translated into applications of content distribution, multiple-user authorization and confidential information transferring and storing.
The thesis summarizes the progress of optical information security and introduces advances of image encryption by optical system and techniques. Based on these widely used optical encoding systems and hiding technologies, we proposed to encrypt and hide multiple images compressively and meanwhile resolve key related problems systematically and completely. In the thesis, we started with the fundamental analysis of optical information processing to verify the feasibility and performance. Then the computational optics was involved to introduce the techniques originated from optical information processing into the application, such as specific domain hidden in optics. The physical optical system was used to demonstrate the algorithms and performance in terms of parallel processing in optics. Major contributions covers four aspects as follows,
1) Multiple images are scanned and recorded simultaneously based on digital holography simulating optical scanning holography. The encryption is further improved by multiplexing the diffraction distance and applying masks to shuffle the distribution of complex amplitude of digital holograms. The decryption is modeled by an inverse problem and the solution is optimized by the Tikhonov regularization. The results from numerical experiments demonstrates the feasibility, robustness and security of the algorithm and the reconstruction of images is advantageous over existing algorithms.
2) Taking advantage of compressive hologram, it is roposed to compress encrypted holograms by non-uniform down sampling. In the algorithm, we deduce the optical transfer function of the optical scanning holography and reveal the function analogous to certain kind of Fourier transform. Furthermore, owing to the sparsity of natural images under wavelet decomposition and the incoherence between wavelet sparsity operator and Fourier operator, a non-uniform down sampling of Fourier holograms is guaranteed to reconstruct original images based on the compressive sensing theory. Finally, the reconstruction is implemented by solving an inverse problem with a sparse constraint.
3) Total variation is involved to reconstructing imaged with fine edges and wavelet processing is employed as a pre-processing step to record information of multiple images. The above algorithm lays a foundation for an encryption strategy by a compressive hologram. Here the solving operation is optimized with a total variation to achieve images with edges in replace of a12norm. In order to reduce the cross-talk effect during scanning multiple images, the wavelet decomposition is utilized as a pre-processing step to avoid overlapping of multiple image information, which ensures the information of images recorded completely. Not only is the algorithm demonstrated by a simulation, but also it is implemented in a physical optical scanning holography system. These experiments verifies the algorithm, investigate the compressive capability and reconstruction quality.
4) The phase retrieval algorithm realizes the multiple-image hiding with less lenses. Phase filters are involved in the algorithm to hide several image by frequency multiplexing. It outputs an image containing all frequency information of images. The phase retrieval method is introduced to find a specific phase mask to modulate the image similar to the carrier image and we take the correlation coefficient as the threshold. Finally, the carrier image is displaced into the right position and original secret images are extracted with the corresponding mask and phase filters. Numerical experiment demonstrates the feasibility of the algorithm and analyze the recognition of hiding information and the convergence of phase retrieval algorithm.
引文
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