Broadband Hyperspectral Phase Retrieval From Noisy Data
Katkovnik, Vladimir; Shevkunov, Igor; Egiazarian, Karen (2020-09)
Katkovnik, Vladimir
Shevkunov, Igor
Egiazarian, Karen
IEEE
09 / 2020
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202110197708
https://urn.fi/URN:NBN:fi:tuni-202110197708
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [16654]