@inbook{0669bb837551432b8dcc29d4e416dda7,
title = "An iterative blind source separation method for convolutive mixtures of images",
abstract = "The paper deals with blind source separation of images. The model which is adopted here is a convolutive multi-dimensional one. Recent results about polynomial matrices in several indeterminates are used to prove the invertibility of the mixing process. We then extend an iterative blind source separation method to the multi-dimensional case and show that it still applies if the source spectra vanish on an interval. Based on experimental observations we then discuss problems arising when we want to separate natural images: the sources are non i.i.d. and have a band limited spectrum; a scalar filtering indeterminacy thus remains after separation.",
author = "Marc Castella and Pcsquet, \{Jean Christophe\}",
year = "2004",
month = jan,
day = "1",
doi = "10.1007/978-3-540-30110-3\_116",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "922--929",
editor = "Puntonet, \{Carlos G.\} and Alberto Prieto",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}