基于神经网络的混沌虹膜相位掩模计算全息加密图像恢复  

Neural network-based computational holographic encryption image reconstruction scheme for chaotic iris phase mask

作　　者：胡涛 孙雪茹 金伟民[1,2] HU Tao;SUN Xueru;JIN Weimin(Institute of Information Optics,College of Physics and Electronic Information Engineering,Zhejiang Normal University,Jinhua 321004,China;Key Laboratory of Optical Information Detecting and Display Technology in Zhejiang Province,Jinhua 321004,China)

机构地区：[1]浙江师范大学物理与电子信息工程学院信息光学研究所,浙江金华321004 [2]浙江省光信息检测与显示技术研究重点实验室,浙江金华321004

出　　处：《光学精密工程》2023年第3期417-428,共12页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.61377010,No.61205012);浙江省自然科学基金资助项目(No.LY17F050002)。

摘　　要：为了拓展对计算全息加密图像的解密方法,针对非法攻击难度大的对称-非对称混合加密系统,提出了一种利用神经网络恢复混沌虹膜相位掩模计算全息加密图像的方案。对明文图像进行加密,生成计算全息的密文图像,制作大量的密文明文图像对作为数据集。通过搭建神经网络不断地训练和测试,训练完成后的神经网络可以拟合出密文图像到明文图像的映射关系,解密时不再使用公钥和私钥对密文图像进行解密。实验结果表明:通过神经网络恢复出的图像与明文图像相比,平均互相关系数为0.984,平均峰值信噪比为61.0 dB,平均结构相似性为0.77;对密文图像进行噪声污染,也可以恢复出较高质量的图像,实现了通过神经网络对密文图像解密的目的,方案是可行的并具有较好的鲁棒性。To expand the decryption method of computational holographic encrypted images for a symmetric-asymmetric hybrid encryption system that cannot be easily attacked illegally,a scheme involving the use of a neural network to restore chaotic iris phase mask computational holographic encrypted images is proposed.First,a plaintext image is encrypted and a ciphertext image of a computational hologram is generated.Next,numerous ciphertext image pairs are generated as datasets.Subsequently,they are continuously trained and tested by using them to build a neural network.Results show that the trained neural network can fit the mapping relationship from the ciphertext image to the plaintext image and that the public or private key is no longer used to decrypt the ciphertext image during decryption.Additionally,the average cross-correlation coefficient is 0.984,the average peak signal-to-noise ratio is 61.0 dB,and the average structural similarity is 0.77,which indicate better performances compared with the performances of a plaintext image recovered by the neural network.By polluting the ciphertext image with noise,a higher quality image is obtained.The purpose of decrypting a ciphertext image via a neural network is achieved,and the scheme is shown to be feasible and robust.

关 键 词：计算全息 光学加密 深度学习 生物密码 混沌 残差网络 

分 类 号：O438.1[机械工程—光学工程] TP309.7[理学—光学]