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Hyperspectral phase imaging with denoising in SVD image subspace

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Abstract

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.

© 2019 The Author(s)

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