Hyperspectral phase retrieval

Vladimir Katkovnik; Igor Shevkunov; Karen Eguiazarian

doi:10.1117/12.2553713

30 March 2020 Hyperspectral phase retrieval

Vladimir Katkovnik, Igor Shevkunov, Karen Eguiazarian

Proceedings Volume 11351, Unconventional Optical Imaging II; 113511G (2020) https://doi.org/10.1117/12.2553713
Event: SPIE Photonics Europe, 2020, Online Only

Abstract

Hyperspectral (HS) imaging retrieves information from data obtained across a broad spectral range of spectral channels. The object to reconstruct is a 3D cube, where the two coordinates are spatial and the 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 spectra. HS phase retrieval is formulated as a reconstruction of an HS complex-valued object cube from Gaussian noisy intensity observations. The considered observation model, projections of the object on the sensor plane, includes varying delay operators such that identical but mutually phase-shifted broadband copies of the object are interfering at the sensor plane. The derived iterative algorithm includes an original proximity spectral analysis operator and sparsity modeling for complex-valued 3D cubes. It is demonstrated that the HS phase retrieval problem can be resolved without random phase coding of wavefronts typical for the conventional phase retrieval techniques. The performance of the new algorithm for phase imaging is demonstrated in simulation tests and in the processing of experimental data.

Conference Presentation

Citation Download Citation

Vladimir Katkovnik, Igor Shevkunov, and Karen Eguiazarian "Hyperspectral phase retrieval", Proc. SPIE 11351, Unconventional Optical Imaging II, 113511G (30 March 2020); https://doi.org/10.1117/12.2553713

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available