NeuWS: Neural wavefront shaping for guidestar-free imaging through static and dynamic scattering media
Abstract
Diffraction-limited optical imaging through scattering media has the potential to transform many applications such as airborne and space-based imaging (through the atmosphere), bioimaging (through skin and human tissue), and fiber-based imaging (through fiber bundles). Existing wavefront shaping methods can image through scattering media and other obscurants by optically correcting wavefront aberrations using high-resolution spatial light modulators—but these methods generally require (i) guidestars, (ii) controlled illumination, (iii) point scanning, and/or (iv) statics scenes and aberrations. We propose neural wavefront shaping (NeuWS), a scanning-free wavefront shaping technique that integrates maximum likelihood estimation, measurement modulation, and neural signal representations to reconstruct diffraction-limited images through strong static and dynamic scattering media without guidestars, sparse targets, controlled illumination, nor specialized image sensors. We experimentally demonstrate guidestar-free, wide field-of-view, high-resolution, diffraction-limited imaging of extended, nonsparse, and static/dynamic scenes captured through static/dynamic aberrations.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 30, 2023
- Source ID
- 10.1126/sciadv.adg4671
Entities
People
- Ashok Veeraraghavan
- Brandon Y. Feng
- Christopher A. Metzler
- Haiyun Guo
- Manoj K Sharma
- Mingyang Xie
- Vivek Boominathan
Organizations
- Rice University
- University of Maryland