Snapshot Compressive Imaging: From Theory to Applications

On March 21, 2025, our group was honored to host Prof. Xin Yuan from the School of Engineering at Westlake University for an engaging academic seminar titled “Snapshot Compressive Imaging: From Theory to Applications.”

Prof. Yuan is a leading expert in the field of computational imaging and compressive sensing. During his presentation, he provided a comprehensive overview of his team’s significant contributions to Snapshot Compressive Imaging (SCI), focusing on:

• Hardware-Algorithm Co-design: Innovative architectures for capturing high-dimensional data (video, hyperspectral) using 2D detectors through coded apertures.
• Deep Learning for SCI: The transition from traditional optimization-based reconstruction to state-of-the-art deep learning models (such as PnP-ADMM and Transformers) for real-time, high-quality recovery.
• Clinical and Industrial Applications: How SCI technology is revolutionizing ultra-high-speed photography and biomedical imaging, providing new tools for observing fast-evolving biological processes.

The seminar concluded with an interactive session where members of the Random Matrix Optics Research Group (RMORG) discussed the potential of combining SCI with statistical optics to tackle deep-tissue imaging challenges. We extend our gratitude to Prof. Yuan for sharing his visionary work.