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Hyperspectral phase imaging based on denoising in complex-valued eigensubspace

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Artikkeli105973
Sivumäärä10
JulkaisuOptics and Lasers in Engineering
Vuosikerta127
Varhainen verkossa julkaisun päivämäärä6 joulukuuta 2019
DOI - pysyväislinkit
TilaE-pub ahead of print - 6 joulukuuta 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

A novel algorithm for reconstruction of hyperspectral 3D complex domain images (phase/amplitude) from noisy complex domain observations has been developed and studied. This algorithm starts from the SVD (singular value decomposition) analysis of the observed complex-valued data and looks for the optimal low dimension eigenspace. These eigenspace images are processed based on special non-local block-matching complex domain filters. The accuracy and quantitative advantage of the new algorithm for phase and amplitude imaging are demonstrated in simulation tests and in processing of the experimental data. It is shown that the algorithm is effective and provides reliable results even for highly noisy data.