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Communication Dans Un Congrès Année : 2016

Minimum distance criterion for non negative hyperspectral image

Yingying Song
David Brie
Simon Henrot
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Résumé

This work aims at studying a method to automatically estimate regularization parameters of hyperspectral images deconvolution methods. The deconvolution problem is formulated as a multi-objective optimization problem and the properties of the corresponding response surface are studied. Based on these properties, the minimum distance criterion (MDC) is proposed to estimate regularization parameters. It has good theoretical properties (uniqueness, robustness) from which a grid search based approach is proposed. It results in a fast approach to estimate the regularization parameters.
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Dates et versions

hal-01266980 , version 1 (03-02-2016)

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  • HAL Id : hal-01266980 , version 1

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Yingying Song, David Brie, El-Hadi Djermoune, Simon Henrot. Minimum distance criterion for non negative hyperspectral image. 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Mar 2016, Shanghai, China. ⟨hal-01266980⟩
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