Mismatched sparse denoiser requires overestimating the support length

Giulio Coluccia 1 Aline Roumy 2 Enrico Magli 1
2 Sirocco - Analysis representation, compression and communication of visual data
Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : A well-known result [1, Lemma 3.4] states that, without noise, it is better to overestimate the support of a sparse signal, since, if the estimated support includes the true support, the reconstruction is perfect. In this paper, we investigate whether this result holds also in the presence of noise. First, we derive the covariance matrix of the signal estimate when the observation matrix is Gaussian, generalizing existing results. Then, we show that, even in the noisy case, overestimating the support length is the preferred solution, as the error incurred by missing some signal components dominates the overall error variance. Finally, an upper bound of the estimated support length is provided to avoid excessive noise amplification.
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Communication dans un congrès
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. 2017, 〈10.1109/ICASSP.2017.7953058〉
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Soumis le : lundi 18 septembre 2017 - 17:52:54
Dernière modification le : mercredi 16 mai 2018 - 11:24:14

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Giulio Coluccia, Aline Roumy, Enrico Magli. Mismatched sparse denoiser requires overestimating the support length. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. 2017, 〈10.1109/ICASSP.2017.7953058〉. 〈hal-01589633〉

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