计算成像是一个将计算算法与智能光学设计相结合的前沿领域，它能够从视觉数据中提取比传统成像方法更多的信息。该技术的目标在于克服传统2D成像的局限性，后者可能受到像差、噪声和曝光时间等物理因素的限制。然而，大多数计算成像技术仅适用于通用场景。我们提出的元成像传感器和宽视场波前传感器，能够在多种应用中实现多点像差估计和校正，而无需对光学前端进行任何额外的硬件改动。我们的方法为计算成像技术在遥感、天文观测、工业检测、自动驾驶和精准医疗等领域的应用开辟了新的道路。

代表性论文

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• Super-resolution imaging of fluorescent dipoles via polarized structured illumination microscopy, Nature communications 2019

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