论文信息 - Coherent-Image Reconstruction Using Convolutional Neural Networks - 字舞流文

Coherent-Image Reconstruction Using Convolutional Neural Networks

We describe a technique for incorporating convolutional-neural-network models into a comprehensive approach for coherent-image reconstruction in the presence of noise and phase errors using the consensus equilibrium framework.

Charles A. Bouman | Mark F. Spencer | Casey J. PeUizzari

[1] Charles A. Bouman,et al. Plug-and-Play Unplugged: Optimization Free Reconstruction using Consensus Equilibrium , 2017, SIAM J. Imaging Sci..

[2] L. Andrews,et al. Laser Beam Propagation Through Random Media , 1998 .

[3] Charles A. Bouman,et al. Consensus Equilibrium: A Framework for Model Integration , 2018 .

[4] Lei Zhang,et al. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising , 2016, IEEE Transactions on Image Processing.

[5] Casey J. Pellizzari,et al. Imaging through distributed-volume aberrations using single-shot digital holography. , 2019, Journal of the Optical Society of America. A, Optics, image science, and vision.

[6] Charles A. Bouman,et al. Phase-error estimation and image reconstruction from digital-holography data using a Bayesian framework , 2017, Journal of the Optical Society of America. A, Optics, image science, and vision.