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Snapshot Hyperspectral Imaging via Compressive Sensing and Implicit Neural Representation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a snapshot hyperspectral imaging method using randomized aperture codes and implicit neural representations. It shows high performance across a range of hyperspectral datasets, without any external supervision or cross-band information.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2025 in Proceedings Optica Imaging Congress 2025, 3D, DH, COSI, IS, pcAOP, RadIT - Part of Optica Imaging Congress
PublisherOptical Society of America
ISBN (Electronic)9781557529374
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 Computational Optical Sensing and Imaging, COSI 2025 - Seattle, United States
Duration: Aug 18 2025Aug 21 2025

Publication series

NameComputational Optical Sensing and Imaging, COSI 2025 in Proceedings Optica Imaging Congress 2025, 3D, DH, COSI, IS, pcAOP, RadIT - Part of Optica Imaging Congress

Conference

Conference2025 Computational Optical Sensing and Imaging, COSI 2025
Country/TerritoryUnited States
CitySeattle
Period8/18/258/21/25

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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