End-to-End Optimization of Metasurfaces for Imaging with Compressed Sensing
We present a framework for the end-to-end optimization of metasurface imaging systems that reconstruct targets using compressed sensing, a technique for solving underdetermined imaging problems when the target object exhibits sparsity (e.g., the object can be described by a small number of nonzero v...
| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
American Chemical Society
2024
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| Online Access: | https://hdl.handle.net/1721.1/155313 |