G03H2001/0875

DEEP LEARNING-BASED DIGITAL HOLOGRAPHIC CONTINUOUS PHASE NOISE REDUCTION METHOD FOR MICROSTRUCTURE MEASUREMENT

A deep learning-based digital holographic continuous phase noise reduction method for microstructure measurement is provided. A MEMS microstructure is simulated to generate an object phase image through generation of random matrix superposition, noise in a digital holographic continuous phase map is simultaneously simulated to generate a noise grayscale image, and a simulation data set is thus created. An end-to-end convolutional neural network is designed, and a trained convolutional neural network is trained and obtained. A holographic interference pattern of an object under measurement is collected by photographing, and after spectrum extraction, angular spectrum diffraction, phase unwrapping, and distortion compensation, a continuous phase map containing only the object phase and noise is obtained and input into the trained convolutional neural network to obtain an object phase map. A simulation data set is accurately created in the disclosure, thereby the difficulty of collecting a large amount of experimental data is avoided.

METHOD FOR PHASE RETRIEVAL TO REDUCE A SAMPLING REQUIREMENT WHEN IMAGING A DYNAMIC PROCESS

A method for retrieving phase information in a coherent diffraction imaging process includes acquiring a plurality of 3D data sets, each 3D data set corresponding to one of a plurality of time states, and reconstructing a 3D image of the object at a given time state using the 3D data set from all of the time states. Each 3D data set is acquired by: illuminating an object positioned in a first position with a coherent beam; measuring a first 2D diffraction pattern using an area detector; rotating the object around a tilt axis thereof to a second position that is different from the first position; re-illuminating the object positioned in the second position with the coherent beam; re-measuring a second 2D diffraction pattern using the area detector; and repeating the rotating, re-illuminating and re-measuring steps such that each 3D data set includes a predetermined number of diffraction patterns.

Motion compensated multi-wavelength digital holography

A holography imaging system includes a first laser, a second laser, a transmitter optical system, a receiver optical system, and a detector array. The first laser has a constant frequency, and the second laser has a non-constant frequency. The transmitter optical system can illuminate a target simultaneously using portions of the first and second laser signals. The receiver optical system can focus a returned light onto the detector array. A first and second illumination point sources can direct portions of the first and second laser signals onto the detector array. The first and second illumination point sources are located in-plane with a pupil of the receiver optical system. The system can detect simultaneously holograms formed on the detector array based on the returned light and the portions of the first and second laser signals directed by the first and second illumination point sources.