DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval

20 Nov 2020 Eunju Cha Chanseok Lee Mooseok Jang Jong Chul Ye

Fourier phase retrieval is a classical problem of restoring a signal only from the measured magnitude of its Fourier transform. Although Fienup-type algorithms, which use prior knowledge in both spatial and Fourier domains, have been widely used in practice, they can often stall in local minima... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
Residual Connection
Skip Connections
GAN Least Squares Loss
Loss Functions
PatchGAN
Discriminators
Batch Normalization
Normalization
ReLU
Activation Functions
Convolution
Convolutions
Tanh Activation
Activation Functions
Sigmoid Activation
Activation Functions
Instance Normalization
Normalization
Cycle Consistency Loss
Loss Functions
Residual Block
Skip Connection Blocks
Leaky ReLU
Activation Functions
CycleGAN
Generative Models