Image quality for diffraction tomography, holographic backpropagation, and regularized sampling with noisy data

摘要: We consider the behaviour of inverse image reconstruction quality as a function forward data SNR. A canonical scatterer geometry is used to obtain an analytical contrast ratio estimate for Colton–Kirsch regularized sampling. For holographic backpropagation tomography, developed SNR at which transitions from noise-dominated noise-free limit. Numerical results confirm theoretical analyses and extend more complex geometries. Holographic exhibits greatest noise immunity in sense that reconstructed reaches acceptable threshold lower than case standard diffraction tomography or sampling method.