Computational endoscopy—a framework for improving spatial resolution in fiber bundle imaging

John P. Dumas, Muhammad A. Lodhi, Batoul A. Taki, Waheed U. Bajwa, Mark C. Pierce

Research output: Contribution to journalArticlepeer-review

Abstract

This Letter presents a framework for computational imaging (CI) in fiber-bundle-based endoscopy systems. Multiple observations are acquired of objects spatially modulated with different random binary masks. Sparse-recovery algorithms then reconstruct images with more resolved pixels than individual fibers in the bundle. Object details lying within the diameter of single fibers are resolved, allowing images with 41,663 resolvable points to be generated through a bundle with 2,420 fibers. Computational fiber bundle imaging of micro- and macro-scale objects is demonstrated using fluorescent standards and biological tissues, including in vivo imaging of a human fingertip. In each case, CI recovers details that conventional endoscopy does not provide.

Original languageEnglish (US)
Pages (from-to)3968-3971
Number of pages4
JournalOptics Letters
Volume44
Issue number16
DOIs
StatePublished - Aug 15 2019

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

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