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High spatial resolution spectral imaging based on amplitude-phase joint modulation metasurfaces using a global optimization algorithm
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DOI：10.1364/OE.547167.png)
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Conventional spectral imaging techniques relying on dispersive spectrometers are limited by the trade-offs in size, cost, imaging speed, and other factors. Currently, metasurfacebased spectral imaging has attracted considerable attention owing to its miniaturization, real-time detection, and low cost. However, introducing randomness in the spectral response function utilizing guided resonance in metasurfaces requires a large number of periodic elements, resulting in reduced spatial resolution in spectral imaging. Here, we propose a compact miniaturized spectrometer based on an aper iodic metasurface. The response function of the metasurface exhibits a rich variety of features based on the amplitude modulation of optical resonances, which is further enhanced by diffraction effects through phase modulation. By employing a genetic algorithm to optimize the layout of the metasurface, one can achieve low correlation coefficients and a small footprint for spectral encoders, marking a significant improvement in spatial resolution compared to previous metasurface-based spectral imaging approaches. Leveraging the deep learning reconstruction algorithm, we can achieve high-precision spectral recovery in the visible range of 400-700 nm with various narrowband and broadband spectra. The proposed method provides a new idea for hyperspectral imaging technology with high spatial resolution, noise robustness, and fast imaging speed. (c) 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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IF:
3.3
论文数:
6.1W
被引数:
14.3W
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