High-resolution quantitative phase imaging based on a spatial light modulator and incremental binary random sampling

Physics-enhanced neural network for phase retrieval from two diffraction patterns

In this work, we propose a physics-enhanced two-to-one Y-neural network (two inputs and one output) for phase retrieval of complex wavefronts from two diffraction patterns. The learnable parameters of the Y-net are optimized by minimizing a hybrid loss function, which evaluates the root-mean-square error and normalized Pearson correlated coefficient on the two diffraction planes. An angular spectrum method network is designed for self-supervised training on the Y-net. Amplitudes and phases of wavefronts diffracted by a USAF-1951 resolution target, a phase grating of 200 lp/mm, and a skeletal muscle cell were retrieved using a Y-net with 100 learning iterations. Fast reconstructions could be realized without constraints or a priori knowledge of the samples.

Phase retrieval by random binary amplitude modulation and ptychography principle

An improved binary amplitude modulation-based phase retrieval method studied by means of simulations and experiments is presented in this paper. The idea of ptychography is introduced for the purpose of designing random binary amplitude masks. The masks have the features that part of the light transmission regions is overlapped with each other and the overlapping positions are randomly distributed. The requirement for the consistency of light field in overlapping regions forms a strong constraint which is similar to the overlap constraint in ptychography. The constraint makes the iterative algorithm have high convergence accuracy in comparison to that of the original binary amplitude modulation method. Influences of amounts and overlap ratio of the modulation mask on reconstruction accuracy and speed of imaging process are analyzed. The comparison between our method and the original binary amplitude modulation method is performed in order to verify the feasibility of the proposed method.

Complex wavefront sensing based on coherent diffraction imaging using vortex modulation

Phase retrieval seeks to reconstruct the phase from the measured intensity, which is an ill-posed problem. A phase retrieval problem can be solved with physical constraints by modulating the investigated complex wavefront. Orbital angular momentum has been recently employed as a type of reliable modulation. The topological charge l is robust during propagation when there is atmospheric turbulence. In this work, topological modulation is used to solve the phase retrieval problem. Topological modulation offers an effective dynamic range of intensity constraints for reconstruction. The maximum intensity value of the spectrum is reduced by a factor of 173 under topological modulation when l is 50. The phase is iteratively reconstructed without a priori knowledge. The stagnation problem during the iteration can be avoided using multiple topological modulations.

Complex wavefront sensing based on alternative structured phase modulation

Spatial light modulators (SLMs), which generate varying phase modulation, are widely used in coherent diffraction imaging. Random patterns are uploaded on the SLM to modulate the measured wavefront. However, a random pattern is highly complex and requires a reliable SLM. In addition, the uncorrelated terms generated from the random modulations need to be sufficiently captured using an imaging sensor with a high signal-to-noise ratio (SNR) to avoid stagnation during iterations. We propose an alternative structured phase modulation (ASPM) method. The modulations are composed of orthogonally placed phase bars that introduce uncorrelated modulations. The ASPM modulation can act as the phase grating; in addition, the modulated intensities are concentrated, which can be captured with a high SNR. The complexity of the ASPM patterns is significantly reduced, which is helpful for utilizing the SLM to generate reliable phase modulation.