@inproceedings{3dd9fe0d30994547b36da198d8575214,
title = "Two distributed algorithms for the deconvolution of large radio-interferometric multispectral images",
abstract = "We address in this paper the deconvolution issue for radiointerferometric multispectral images. Whereas this problem has been widely explored in the recent literature for single images, a few algorithms are able to reconstruct multispectral images (three-dimensional images) [1], [2]. We propose in this paper two new distributed algorithms based on the optimization methods ADMM and projected gradient (PG) for the reconstruction of radio-interferometric multispectral images. We present an original distributed architecture and a comparison of their performance on a quasi-real data cube.",
keywords = "ADMM, Deconvolution, Distributed optimization, Multispectral images, Projected gradient, Radio-interferometry",
author = "C{\'e}line Meillier and Pascal Bianchi and Walid Hachem",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 24th European Signal Processing Conference, EUSIPCO 2016 ; Conference date: 28-08-2016 Through 02-09-2016",
year = "2016",
month = nov,
day = "28",
doi = "10.1109/EUSIPCO.2016.7760344",
language = "English",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
pages = "728--732",
booktitle = "2016 24th European Signal Processing Conference, EUSIPCO 2016",
}