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The resolution optimization and sampling strategies in practical digital in-line holography (DIH) with spherical wave illumination are analytically studied by optimizing system parameters. Optimal parameters of holographic recording, including illumination wavelength, numerical aperture of the spherical illumination wave, source-sensor distance, object–sensor distance, and sampling parameters of the sensor, for achievable resolution are worked out. A formula is derived to guide the DIH system design in general cases. Different sampling strategies associated with corresponding reconstruction waves (plane wave and spherical waves with various curvatures) are analyzed. The reason why recording with spherical wave and reconstructing with plane wave works well in practice is explained in detail. We also present how to determine the reconstruction distance and magnification to reconcile the curvature difference. The analysis is carried out mathematically and verified by simulated holograms. Optical experiments with U.S. Air Force resolution target are carried out based on the analysis for further verification.
Tracking and imaging humans on heterogeneous infrared sensor arrays for law enforcement applications
Conventional optical design assumes that images are formed by optical processing and sampled by electronic focal planes. Computational design, in contrast, assumes that optical processing forms coded patterns that are decoded into images by digital processing. This course explains design principles and applications of computational optical imaging systems. The course covers four critical tools for computational imager design: (1) radiation field models, (2) discrete sampling models, (3) coding, regularization and inverse problems and (4) optical element design and applies these tools in analyzing example computational systems for spectral, 3D and wide field imaging.
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