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Image compression and encryption scheme based on 2D compressive sensing and fractional Mellin transform

机译:基于二维压缩感知和分数梅林变换的图像压缩加密方案

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摘要

Most of the existing image encryption techniques bear security risks for taking linear transform or suffer encryption data expansion for adopting nonlinear transformation directly. To overcome these difficulties, a novel image compression-encryption scheme is proposed by combining 2D compressive sensing with nonlinear fractional Mellin transform. In this scheme, the original image is measured by measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the nonlinear fractional Mellin transform. The measurement matrices are controlled by chaos map. The Newton Smoothed l(0) Norm (NSL0) algorithm is adopted to obtain the decryption image. Simulation results verify the validity and the reliability of this scheme. (C) 2015 Elsevier B.V. All rights reserved.
机译:现有的大多数图像加密技术都存在进行线性变换的安全风险,或者直接采用非线性变换而遭受加密数据扩展的风险。为了克服这些困难,提出了一种将二维压缩感知与非线性分数梅林变换相结合的新颖的图像压缩加密方案。在该方案中,通过两个方向上的测量矩阵对原始图像进行测量,以同时实现压缩和加密,然后通过非线性分数梅林变换对所得图像进行重新加密。测量矩阵由混沌图控制。采用牛顿平滑l(0)范数(NSL0)算法获得解密图像。仿真结果验证了该方案的有效性和可靠性。 (C)2015 Elsevier B.V.保留所有权利。

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