Long-Range, Large Aperture Thermal Imaging via Sparse Aperture Metalens Computational Imaging
| dc.contributor.advisor | Veeraraghavan, Ashok | en_US |
| dc.creator | Wang, Jing | en_US |
| dc.date.accessioned | 2025-01-17T17:24:54Z | en_US |
| dc.date.created | 2024-12 | en_US |
| dc.date.issued | 2024-12-03 | en_US |
| dc.date.submitted | December 2024 | en_US |
| dc.date.updated | 2025-01-17T17:24:54Z | en_US |
| dc.description.abstract | Long-range imaging in the mid-wave infrared (MWIR) is critical for defense, industrial, and environmental applications, often requiring high-resolution imaging achievable only with large-aperture lenses (~100–1000 mm). Conventional glassbased refractive optics meet these equirements but result in bulky, costly systems. While metalenses offer a lightweight alternative, creating large apertures with current fabrication techniques poses significant challenges. To address this, we employed a computational imaging approach using sparse aperture metalenses. By arranging an array of small metalenses in a spatial configuration that maximizes spatial information and applying a computational reconstruction algorithm, our system achieves high-resolution, high-contrast images equivalent to those from a single large aperture. This scalable approach allows large-aperture realization by strategically arranging smaller sub-apertures. We validated this design with a prototype of 89 mm outer diameter and 356 mm focal length. Enhanced with a neural network-based reconstruction algorithm, our proposed sparse aperture system achieves near-diffraction-limited performance. Furthermore, simulations of a large recursive sparse aperture demonstrate improved MTF coverage and higher resolution imaging. This work represents progress toward practical, scalable, high-performance MWIR imaging systems. | en_US |
| dc.embargo.lift | 2030-12-01 | en_US |
| dc.embargo.terms | 2030-12-01 | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/118236 | en_US |
| dc.language.iso | en | en_US |
| dc.subject | MWIR | en_US |
| dc.subject | Computational imaging | en_US |
| dc.subject | Meta-optic | en_US |
| dc.subject | Long-range imaging | en_US |
| dc.subject | Optical sparse aperture | en_US |
| dc.title | Long-Range, Large Aperture Thermal Imaging via Sparse Aperture Metalens Computational Imaging | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Electrical and Computer Engineering | en_US |
| thesis.degree.discipline | Electrical & Computer Eng., Electrical & Computer Eng. | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science | en_US |