Hyperspectral imaging provides high-dimensional spatial–temporal–spectral information showing intrinsic matter characteristics^1,2,3,4,5. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution. By integrating different broadband modulation materials on the image sensor chip, the target spectral information is non-uniformly and intrinsically coupled to each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following this framework, we fabricated a broadband visible–near-infrared (400–1,700 nm) hyperspectral image sensor using photolithography, with an average light throughput of 74.8% and 96 wavelength channels. The demonstrated resolution is 1,024 × 1,024 pixels at 124 fps. We demonstrated its wide applications, including chlorophyll and sugar quantification for intelligent agriculture, blood oxygen and water quality monitoring for human health, textile classification and apple bruise detection for industrial automation, and remote lunar detection for astronomy. The integrated hyperspectral image sensor weighs only tens of grams and can be assembled on various resource-limited platforms or equipped with off-the-shelf optical systems. The technique transforms the challenge of high-dimensional imaging from a high-cost manufacturing and cumbersome system to one that is solvable through on-chip compression and agile computation.

高光谱成像提供高维空间-时间-光谱信息，显示内禀物质特征^1,2,3,4,5。在这里，我们报告了一个具有高空间和时间分辨率的片上计算高光谱成像框架。通过在图像传感器芯片上集成不同的宽带调制材料，目标光谱信息以非均匀和本质耦合到每个像素，具有高光通量。利用智能重建算法，可以从每一帧中恢复多通道图像，实现实时高光谱成像。按照这个框架，我们使用光刻技术制造了一种宽带可见光-近红外 （400-1,700 nm） 高光谱图像传感器，平均光通量为 74.8%，具有 96 个波长通道。演示的分辨率为 1,024 × 1,024 像素，帧率为 124 fps。我们展示了它的广泛应用，包括用于智能农业的叶绿素和糖定量、用于人类健康的血氧和水质监测、用于工业自动化的纺织品分类和苹果瘀伤检测，以及用于天文学的远程月球检测。集成的高光谱图像传感器仅重数十克，可以组装在各种资源有限的平台上或配备现成的光学系统。该技术将高维成像的挑战从高成本和繁琐的系统转变为可通过片上压缩和敏捷计算解决的系统。