Many applications requiring both spectral and spatial information at high resolution benefit from spectral imaging. Although different technical methods have been developed and commercially available, computational spectral cameras represent a compact, lightweight, and inexpensive solution. However, the tradeoff between spatial and spectral resolutions, dominated by the limited data volume and environmental noise, limits the potential of these cameras. In this study, we developed a deeply learned broadband encoding stochastic hyperspectral camera. In particular, using advanced artificial intelligence in filter design and spectrum reconstruction, we achieved 7000–11,000 times faster signal processing and ~10 times improvement regarding noise tolerance. These improvements enabled us to precisely and dynamically reconstruct the spectra of the entire field of view, previously unreachable with compact computational spectral cameras.

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Computational spectroscopic instruments with broadband encoding stochastic (BEST) filters allow the reconstruction of the spectrum at high precision with only a few filters. However, conventional design manners of BEST filters are often heuristic and may fail to fully explore the encoding potential of BEST filters. The parameter constrained spectral encoder and decoder (PCSED)—a neural network‐based framework—is presented for the design of BEST filters in spectroscopic instruments. By incorporating the target spectral response definition and the optical design procedures comprehensively, PCSED links the mathematical optimum and practical limits confined by available fabrication techniques. Benefiting from this, a BEST‐filter‐based spectral camera presents a higher reconstruction accuracy with up to 30 times enhancement and a better tolerance to fabrication errors. The generalizability of PCSED is validated in designing metasurface‐ and interference‐thin‐film‐based BEST filters.

In super-resolution optical microscopes, aberrations often compromise the image performances by reducing its resolution and contrast. In previous works, the aberrations in stimulated emission depletion (STED) microscopy and single-molecule localization microscopy (SMLM) have been well-investigated, while the research on the aberrations in structured illumination microscopy (SIM) is not sufficient, the researchers always poured attention into aberrations only in the detection path. In this paper, we investigate the aberrations in SIM in a comprehensive manner, and their causes and effects on both the illumination and the detection paths are discussed. The aberrations in the illumination path may distort illumination patterns, and deteriorate the final images, together with the aberrations in the detection path. In addition, several non-aberration-related factors, especially the misalignment of the incident beams with respect to the objective pupil, can also dramatically influence the performances of SIM. The analysis provides the theoretical basis and for optimizing a SIM system.

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In using a laser light source, it becomes possible to realize an ultra-wide display gamut that approaches the human color vision limit. This paper introduces a method for extremely large gamut optimization for different primary numbers, and it offers a primary set that produces a nearly ultimate gamut. Considering display lightness, we calculated wavelength selection and lightness design of a display with 3-9 primaries in the CIELAB uniform color space (UCS) by optimizing the coverage of the optimal color gamut. Theoretically the maximum gamut area of a laser display with 3-12 primaries in the CIE xy and CIE u'v' chromaticity diagrams is also calculated for comparison. We recommend 6 primaries as a reasonable choice, since the coverage reaches 97.6% of the optimal color. Taking into account the luminance efficacy of radiation (LER) and feasible laser wavelengths in practice, we get a practical design of wavelengths and power for a laser projection display with 6 primaries, which covers 96.6% of the optimal color gamut.

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This paper introduces a method for an extremely wide display gamut optimization for different primary numbers. Considering luminance efficacy of radiation (LER), the method can be used in primitive color design for a practical display, especially in multi‐primary ultra‐wide gamut displays such as QD‐LED or laser display.