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- W2308961925 abstract "In this paper, we study the compressive sensing effects on 2D signals exhibiting sparsity in 2D DFT domain. A simple algorithm for reconstruction of randomly undersampled data is proposed. It is based on the analytically determined threshold that precisely separates signal and non-signal components in the 2D DFT domain. The algorithm operates fast in a single iteration providing the accurate signal reconstruction. In the situations that are not comprised by the analytic derivation and constrains, the algorithm is still efficient and need just a couple of iterations. The proposed solution shows promising results in ISAR imaging (simulated data are used), where the reconstruction is achieved even in the case when less than 10 % of data are available." @default.
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- W2308961925 date "2016-07-18" @default.
- W2308961925 modified "2023-10-16" @default.
- W2308961925 title "An Approach to 2D Signals Recovering in Compressive Sensing Context" @default.
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- W2308961925 doi "https://doi.org/10.1007/s00034-016-0366-8" @default.
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