Resolution-Enhanced Lensless Ptychographic Microscope Based on Maximum-Likelihood High-Dynamic-Range Image Fusion
Li Liu, W. Li, Ming Gong, Lei Zhong, Honggang Gu, Shiyuan Liu
Abstract
The Abbe diffraction limit tells that the resolution of an imaging system is completely determined by the numerical aperture (NA) for a coherent illumination wavelength. Here, a simple-to-implement and noise-robust maximum-likelihood high-dynamic-range (ML-HDR) image fusion approach is proposed to extend the effective NA of the lensless imaging microscope to enhance the resolution of the ptychography. The proposed approach constructs a joint probability to optimize the weighting function through the maximum-likelihood estimation, allowing the direct fusion of the HDR absolute irradiance from a sequence of diffraction frames, dark frames, and exposure times, and it needs no additional and complex parameter calibration and prior modulation templates. The ML-HDR image fusion approach considers mixed noises for the first time, making it proficiently retrieves high-frequency ptychographic signals without losing or reducing the diffraction signal-to-noise ratio in low-frequency regions. A series of simulations and experiments both in transmission and reflection geometries are conducted compared with the single-exposure ptychography, and results indicate that the ML-HDR approach significantly mitigates 8 bits for the detector’s dynamic range and enhances the resolution of ptychographic imaging nearly threefold. Compared with existing HDR techniques based on the linear response function calibration, the proposed ML-HDR demonstrates superior noise immunity and higher reconstruction qualities. These remarkable advancements may greatly broaden the applications of the ML-HDR image fusion approach in lensless computational imaging fields, including but not limited to ankylography, holography and tomography.