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Simulation of different samples size on 2.52THz compressive holographic tomography

Terahertz compressive holographic tomography has been one of the most investigated research topics ever since the generation of terahertz signals. The accuracy of the 3D reconstruction results are influenced by samples size directly. This paper mainly studies that different samples size influence the compressive sensing algorithm iteration number and sparse restriction parameters on the 2.52THz reconstruction results under Gaussian noise conditions. The best reconstruction parameters are given and compared with condition of no noise. This simulation study is possible benefit to the practical application.