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Pré-Publication, Document De Travail Année : 2017

Online deconvolution for pushbroom hyperspectral imaging systems

Yingying Song
Jie Chen
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Cédric Richard
David Brie

Résumé

This paper introduces a framework based on the LMS algorithm for sequential deconvolution of hyperspectral images acquired by pushbroom imaging systems. Considering a sequential model of image blurring phenomenon, we derive a sliding-block regularized LMS algorithm with spatial and spectral regularizers. The performance of the algorithm is evaluated using real hyperspectral data. The role of the hyperparameters is also discussed.
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Dates et versions

hal-01493901 , version 1 (22-03-2017)
hal-01493901 , version 2 (05-02-2018)

Identifiants

  • HAL Id : hal-01493901 , version 1

Citer

Yingying Song, El-Hadi Djermoune, Jie Chen, Cédric Richard, David Brie. Online deconvolution for pushbroom hyperspectral imaging systems. 2017. ⟨hal-01493901v1⟩
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