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By encoding the high-dimensional light-field imaging information into a detectable two-dimensional speckle plane, ghost imaging camera via sparsity constraints (GISC camera) can directly catch the high-dimensional light-field imaging information with only one snapshot. This makes it worth to revisit the spatial resolution limit of this optical imaging system. In this paper we show both theoretically and experimentally that, while the resolution in high-dimensional light-field space is still limited by diffraction, the statistical spatial resolution of GISC camera can be greatly improved comparing to classical Rayleighs criterion by utilizing the discernibility in high-dimensional light-field space. The interaction between imaging resolution, degrees of freedom of light field, and degrees of freedom of objects in high-dimensional light-field space is also demonstrated.
Ghost imaging (GI) is a novel imaging method, which can reconstruct the object information by the light intensity correlation measurements. However, at present, the field of view (FOV) is limited to the illuminating range of the light patterns. To en
A compressive sensing based circular polarization snapshot spectral imaging system is proposed in this paper to acquire two-dimensional spatial, one-dimensional circular polarization (the right and left circular polarization), and one-dimensional spe
A spectral camera based on ghost imaging via sparsity constraints (GISC) acquires a spectral data-cube (x; y; {lambda}) through a single exposure. The noise immunity of the system is one of the important factors affecting the quality of the reconstru
The performance of light-field microscopy is improved by selectively illuminating the relevant subvolume of the specimen with a second objective lens [1-3]. Here we advance this approach to a single-objective geometry, using an oblique one-photon ill
We present a novel diffractive imaging method that harnesses a low-resolution real-space image to guide the phase retrieval. A computational algorithm is developed to utilize such prior knowledge as a real-space constraint in the iterative phase retr