Broadband Hyperspectral Phase Retrieval From Noisy Data

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Abstract

Hyperspectral (HS) imaging retrieves information from data obtained across a wide spectral range of spectral channels. The object to reconstruct is a 3D cube, where two coordinates are spatial and third one is spectral. We assume that this cube is complex-valued, i.e. characterized spatially frequency varying amplitude and phase. The observations are squared magnitudes measured as intensities summarized over spectrum. The HS phase retrieval problem is formulated as a reconstruction of the HS complex-valued object cube from Gaussian noisy intensity observations. The derived iterative algorithm includes the original proximal spectral analysis operator and the sparsity modeling for complex-valued 3D cubes. The efficiency of the algorithm is confirmed by simulation tests.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Image Processing (ICIP)
PublisherIEEE
Pages3154-3158
Number of pages5
ISBN (Electronic)978-1-7281-6395-6
DOIs
Publication statusPublished - Sep 2020
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Image Processing - United Arab Emirates, Abu Dhabi, United Arab Emirates
Duration: 25 Oct 202028 Oct 2020
https://2020.ieeeicip.org

Publication series

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

Conference

ConferenceIEEE International Conference on Image Processing
Abbreviated titleICIP 2020
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period25/10/2028/10/20
Internet address

Publication forum classification

  • Publication forum level 1

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