2020
DOI: 10.18280/ijsse.100510
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Image Encryption Based on Matrix Factorization

Abstract: In this paper, we present a matrix decomposition-based approach for image cryptography. The proposed method consists of decomposing the image into different component and scrambling the components to form the image encryption technique. We use two different type of matrix decomposition techniques to check the efficiency of proposed encryption method. The decomposition techniques used are Independent component analysis (ICA) and Non-Negative Matrix factorization (NMF). The proposed technique has unique user def… Show more

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Cited by 4 publications
(2 citation statements)
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“…Asymmetric color image encryption-decryption was realized using a matrix transformation; however, the throughput was low due to the long encryption-decryption processes [23]. A method of image encryption method based on matrix decompositions is suggested, where the order and rank of the deconstructed components serve as unique key parameters [24]. Wang and Zhang [25] suggested a chaos-controlled poker shuffle operation based method of color image encryption-decryption.…”
Section: Figure 1 Encryption-decryption Processmentioning
confidence: 99%
“…Asymmetric color image encryption-decryption was realized using a matrix transformation; however, the throughput was low due to the long encryption-decryption processes [23]. A method of image encryption method based on matrix decompositions is suggested, where the order and rank of the deconstructed components serve as unique key parameters [24]. Wang and Zhang [25] suggested a chaos-controlled poker shuffle operation based method of color image encryption-decryption.…”
Section: Figure 1 Encryption-decryption Processmentioning
confidence: 99%
“…Research on PET image reconstruction algorithms based on the total variation (TV) model has shown some advancements [10,11]. Several studies have enhanced and expanded the total variation model by adding regularization terms, integrating scale space theory, and utilizing optimization algorithms, achieving promising results on various datasets [12,13].…”
Section: Introductionmentioning
confidence: 99%