Broadband Hyperspectral Phase Retrieval From Noisy Data

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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)
Number of pages5
ISBN (Electronic)978-1-7281-6395-6
Publication statusPublished - Sept 2020
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Image Processing - United Arab Emirates, Abu Dhabi, United Arab Emirates
Duration: 25 Oct 202028 Oct 2020

Publication series

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


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

Publication forum classification

  • Publication forum level 1


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