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Communication Dans Un Congrès Année : 2024

Physically-constrained block-term tensor decomposition for polarimetric image recovery

Résumé

This paper introduces a complete approach for the recovery of polarimetric images from experimental intensity measurements. In many applications, such images collect, at each pixel, a Stokes vector encoding the polarization state of light. By representing a Stokes vector image as a third-order tensor, we propose a new physicallyconstrained block-term tensor decomposition called Stokes-BTD. The proposed model is flexible and comes with broad identifiability guarantees. Moreover, physical constraints ensure meaningful interpretation of low-rank terms as Stokes vectors. In practice, Stokes images must be recovered from indirect, intensity measurements. To this aim, we implement two recovery algorithms for Stokes-BTD based on constrained alternated optimization and highlight constraints related to Stokes vectors. Numerical experiments on synthetic and real data illustrate the potential of the approach.
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Dates et versions

hal-04344657 , version 1 (14-12-2023)
hal-04344657 , version 2 (12-01-2024)

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Paternité

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  • HAL Id : hal-04344657 , version 2

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Saulo Cardoso Barreto, Julien Flamant, Sebastian Miron, David Brie. Physically-constrained block-term tensor decomposition for polarimetric image recovery. International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Apr 2024, Seoul, South Korea. ⟨hal-04344657v2⟩
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