Hyperspectral phase imaging with denoising in SVD image subspace

Vladimir Katkovnik, Igor Shevkunov, Daniel Claus, Giancarlo Pedrini, Karen Egiazarian

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)
3 Downloads (Pure)


We propose a modified denoising algorithm for hyperspectral data. The algorithm is based on a complex domain block-matching 3D filter, on estimation of the noise correlation matrix and on dimension reduction of the Singular Value Decomposition (SVD) eigenspace.
Original languageEnglish
Title of host publicationDigital Holography and Three-Dimensional Imaging 2019
PublisherOptical Society of America
ISBN (Electronic)978-1-943580-59-0
Publication statusPublished - 19 May 2019
Publication typeA4 Article in conference proceedings
EventDigital Holography and Three-Dimensional Imaging -
Duration: 1 Jan 2000 → …


ConferenceDigital Holography and Three-Dimensional Imaging
Period1/01/00 → …

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