Hyperspectral phase imaging with denoising in SVD image subspace

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.