Optimal Measurement Configuration in Computational Diffractive Imaging

Evan Widloski, Ulas Kamaci, Farzad Kamalabadi

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

Abstract

Diffractive lenses have recently been applied to the domain of multispectral imaging in the X-ray and UV regimes where they can achieve very high resolution as compared to reflective and refractive optics. Conventionally, spectral components are reconstructed by taking measurements at the focal planes. However, the reconstruction quality can be improved by optimizing the measurement configuration. In this work, we adapt a sequential backward selection algorithm to search for a configuration which minimizes expected reconstruction error. By approximating the forward system as a circular convolution and making assumptions on the source and noise, we greatly reduce the complexity of the algorithm. Numerical results show that the configuration found by the algorithm significantly improves the reconstruction performance compared to a standard configuration.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
PublisherIEEE Computer Society
Pages281-285
Number of pages5
ISBN (Electronic)9781728163956
DOIs
StatePublished - Oct 2020
Event2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, United Arab Emirates
Duration: Sep 25 2020Sep 28 2020

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2020-October
ISSN (Print)1522-4880

Conference

Conference2020 IEEE International Conference on Image Processing, ICIP 2020
Country/TerritoryUnited Arab Emirates
CityVirtual, Abu Dhabi
Period9/25/209/28/20

Keywords

  • Spectral imaging
  • computational imaging
  • diffractive optics
  • measurement configuration
  • subset selection

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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