基于压缩感知的PWLCM图像加密

Omkar Abhishek, S. N. George, P. Deepthi
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引用次数: 11

摘要

本文将压缩感知与基于混沌密钥的测量矩阵生成相结合,为多媒体安全提供了一种有效的加密算法。基于块的压缩感知通过降低存储需求和复杂性为图像和视频传输领域提供了一种更好的方式,其中多假设预测为提高基于块的压缩感知图像和视频重建过程中的PSNR提供了一种有效的方法。测量矩阵Φ在压缩感知和重建过程中起着至关重要的作用。使用分段线性混沌映射(PWLCM)作为种子生成安全测量矩阵的可能性,然后隐藏初始条件,系统参数,PWLCM的迭代次数作为密钥,使发送方能够在单步压缩中合并加密空间。上述方案提供了高水平的数据安全性,降低了复杂性,压缩具有良好的重构质量,并且减少了随数据发送测量矩阵的负担,进一步降低了整体压缩感知框架的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PWLCM based image encryption through compressive sensing
In this paper, compressive sensing is combined with a chaotic key based generation of measurement matrix to provide an effective encryption algorithm for multimedia security. Block-based compressive sensing provides a better way in the field of image and video transmission by reducing the memory requirements and complexity, where as multiple hypothesis prediction provides a competent way in improving PSNR during reconstruction of block based compressive sensed images and videos. The measurement matrix Φ place a crucial role in this compressive sensing and as well as in the reconstruction process. A possibility to generate secure measurement matrix using piecewise linear chaotic map (PWLCM) as the seed and then hiding initial condition, system parameter, number of iterations of PWLCM as the key enable the sender to incorporate room for encryption along with the compression in a single step. The above mentioned scheme provides high level of data security, reduced complexity, compression with a good reconstruction quality and beside all it reduce the burden of sending the measurement matrix along with the data which further reduces the complexity in over all compressive sensing framework.
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