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• W2113305535 abstract "This paper proposes an efficient image fusion scheme for compressed sensing (CS) imaging, in which fusion is performed on the random projections before reconstruction. Specifically, the measurements of multiple input images are fused into composite measurements via weighted average, in which the weights are calculated based on entropy metrics of the original measurements. Then the fused image with transformation coefficients in a selected basis is reconstructed from the composite measurements by the gradient projection for sparse reconstruction (GPSR) algorithm. The proposed scheme is implemented in a block-based CS framework. Simulation results show that our scheme provides promising fusion performance with a low computational complexity." @default.
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• W2113305535 date "2009-11-01" @default.
• W2113305535 modified "2023-09-30" @default.
• W2113305535 title "Image fusion in compressed sensing" @default.
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• W2113305535 doi "https://doi.org/10.1109/icip.2009.5413866" @default.
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