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Universal Programming of 3D Point Spread Functions for Imaging

UCLA researchers have introduced a framework for synthesizing arbitrary, spatially varying 3D point spread functions (PSFs) using diffractive processors. This approach enables unique imaging capabilities--such as snapshot 3D multispectral imaging--without relying on spectral filters, axial scanning, or digital reconstruction methods. The proposed framework could open up transformative possibilities for computational imaging, optical sensing and spectroscopy, as well as 3D optical information processing.

July 10, 2025


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