Confocal super-resolution microscopy based on a spatial mode sorter

Abstract

Spatial resolution is one of the most important specifications of an imaging system. Recent results in the quantum parameter estimation theory reveal that an arbitrarily small distance between two incoherent point sources can always be efficiently determined through the use of a spatial mode sorter. However, extending this procedure to a general object consisting of many incoherent point sources remains challenging, due to the intrinsic complexity of multi-parameter estimation problems. Here, we generalize the Richardson-Lucy (RL) deconvolution algorithm to address this challenge. We simulate its application to an incoherent confocal microscope, with a Zernike spatial mode sorter replacing the pinhole used in a conventional confocal microscope. We test different spatially incoherent objects of arbitrary geometry, and we find that the resolution enhancement of sorter-based microscopy is on average over 30% higher than that of a conventional confocal microscope using the standard RL deconvolution algorithm. Our method could potentially be used in diverse applications such as fluorescence microscopy and astronomical imaging.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 31, 2021
Source ID
10.1364/oe.419493

Entities

People

  • A. N. Vamivakas
  • Andrew N. Jordan
  • Boris Braverman
  • Jing Yang
  • Katherine K. M. Bearne
  • Robert W. Boyd
  • S. A. Wadood
  • Yiyu Zhou
  • Zhimin Shi

Organizations

  • Canada Excellence Research Chairs
  • Chapman University
  • Defense Advanced Research Projects Agency
  • National Science Foundation
  • Natural Sciences and Engineering Research Council
  • Office of Naval Research
  • University of Ottawa
  • University of Rochester
  • University of South Florida

Tags

Fields of Study

  • Physics

Readers

  • Image Processing and Computer Vision.
  • Nanoscale Plasmonic Nanotechnology
  • Statistical inference.

Technology Areas

  • Quantum Computing