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An Image Compression-Encryption Algorithm Based on Cellular Neural Network and Compressive Sensing

机译:基于细胞神经网络和压缩感知的图像压缩加密算法

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In this paper, an image encryption algorithm on the basis of cellular neural networks (CNN) and compressive sensing (CS) is proposed. Firstly, four CNN with hyper chaotic behavior is introduced to generate chaotic sequence. Then, the index of the sorted chaotic sequence is used to control the generation of measurement matrix in CS procedure. Moreover, Lissajous map is served to produce asymptotic deterministic random measurement matrix instead of the common random measurement matrix. In addition, the chaotic sequence is normalized to 8-bit integer to diffuse the result after applying CS operation on the plain image, and the image after compression and encryption is obtained. The simulation results and analysis verify the proposed algorithm owns good security and ideal performance.
机译:提出了一种基于细胞神经网络(CNN)和压缩感知(CS)的图像加密算法。首先,引入具有超混沌行为的四个CNN来生成混沌序列。然后,在CS过程中,使用排序后的混沌序列的索引来控制测量矩阵的生成。此外,Lissajous映射用于生成渐近确定性随机测量矩阵,而不是公共随机测量矩阵。另外,将混沌序列归一化为8位整数,以在对普通图像进行CS操作之后扩散结果,并且获得压缩和加密之后的图像。仿真结果和分析表明,该算法具有良好的安全性和理想的性能。

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