Image encryption based on Independent Component Analysis and Arnold’s Cat Map

Abstract Security of the multimedia data including image and video is one of the basic requirements for the telecommunications and computer networks. In this paper, a new efficient image encryption technique is presented. It is based on modifying the mixing matrix in Independent Component Analysis (ICA) using the chaotic Arnold’s Cat Map (ACM) for encryption. First, the mixing matrix is generated from the ACM by insert square image of any dimension. Second, the mixing process is implemented using the mixing matrix and the image sources the result is the encryption images that depend on the number of sources. Third, images decrypted using ICA algorithms. We use the Joint Approximate Diagonalization of Eigen-matrices (JADE) algorithm as a case study. The results of several experiments, PSNR, SDR and SSIM index tests compared with standard mixing matrix showed that the proposed image encryption system provided effective and safe way for image encryption.

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