부산대학교 도서관

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 (SNR) 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.