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• W2917004075 abstract "Traditional block compressed sensing (CS) schemes encode nature images via a fixed sampling rate without taking the sparsity level differences among the blocks into consideration. In order to improve sampling efficiency, permutation-based block CS (BCS) schemes are proposed. In these schemes, the crux is to find a good permutation strategy which can make the nonzero entries evenly distributed among the blocks. In order to make the nonzero entries distributed among the blocks as evenly as possible, a novel matrix permutation strategy is proposed in this paper. Then, a BCS scheme with matrix permutation (BCS-MP) is proposed, which can be utilized to encode nature images effectively. Simulation results show that the proposed approach gets a significant gain of peak signal-to-noise ratio (PSNR) of the reconstructed-images compared with the state-of-the-art permutation-based ones and the traditional non-permutation one at the cost of slightly increasing the encoding time." @default.
• W2917004075 created "2019-03-02" @default.
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• W2917004075 date "2019-04-01" @default.
• W2917004075 modified "2023-10-16" @default.
• W2917004075 title "Matrix permutation meets block compressed sensing" @default.
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• W2917004075 doi "https://doi.org/10.1016/j.jvcir.2019.02.023" @default.
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