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- W4283712986 abstract "Image watermarking is a key technology for copyright protection, and how to better balance the invisibility and robustness of algorithms is a challenge. To tackle this challenge, a watermarking optimization method based on matrix decomposition and discrete wavelet transform (DWT) for multi-size images is proposed. The DWT, Hessenberg matrix decomposition (HMD), singular value decomposition (SVD), particle swarm optimization (PSO), Arnold transform and logistic mapping are combined for the first time to achieve an image watermarking optimization algorithm. The multi-level decomposition of DWT is used to be adapted to multi-size host images, the Arnold transform, logistic mapping, HMD and SVD are used to enhance the security and robustness, and the PSO optimized scaling factor to balance invisibility and robustness. The simulation results of the proposed method show that the PSNRs are higher than 44.9 dB without attacks and the NCs are higher than 0.98 under various attacks. Compared with the existing works, the proposed method shows high robustness against various attacks, such as noise, filtering and JPEG compression and in particular, the NC values are at least 0.44% higher than that in noise attacks." @default.
- W4283712986 created "2022-06-30" @default.
- W4283712986 creator A5000146054 @default.
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- W4283712986 date "2022-06-28" @default.
- W4283712986 modified "2023-09-30" @default.
- W4283712986 title "A Watermarking Optimization Method Based on Matrix Decomposition and DWT for Multi-Size Images" @default.
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- W4283712986 doi "https://doi.org/10.3390/electronics11132027" @default.
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