With the development of the new generation of information technology, computational imaging has emerged. It acquires encoded light field information in multiple dimensions, opening up a new paradigm for sensor design. In January 2023, Alibaba's DAMO Academy listed computational optical imaging as one of the top ten technological trends for 2023. This emerging technology has achieved numerous results, such as super-resolution fluorescence microscopy in 2014 and cryo-electron microscopy in 2017, which won the Nobel Prize. Through the collaborative optimization of the optical system and signal processing algorithms, it has achieved the imaging functions of high resolution, large field of view and multi-modal. From single-pixel imaging to compressive sensing imaging, from light field imaging to computational holography, a series of innovative technologies have continuously expanded the boundaries of imaging, bringing new opportunities to numerous fields such as scientific research, medical care, and industrial inspection.

Computational spectroscopy technology integrates the concept of computational imaging and focuses on the precise analysis and utilization of the spectral information of light. With hyperspectral and hyperspectral imaging technologies, we can obtain the rich spectral features of the target object, as if we have drawn a unique "fingerprint map" for it. This plays an irreplaceable role in fields such as environmental monitoring, agricultural remote sensing, and food safety testing, helping us accurately identify material components and monitor ecological changes.