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  Inlier-based ICA with an application to superimposed images

Meinecke, F., Harmeling, S., & Müller, K.-R. (2005). Inlier-based ICA with an application to superimposed images. International Journal of Imaging Systems and Technology, 15(1), 48-55. doi:10.1002/ima.20037.

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Meinecke, F, Author
Harmeling, S1, Author           
Müller, K-R1, Author           
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1External Organizations, ou_persistent22              

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 Abstract: This paper proposes a new independent component analysis (ICA) method which is able to unmix overcomplete mixtures of sparce or structured signals like speech, music or images. Furthermore, the method is designed to be robust against outliers, which is a favorable feature for ICA algorithms since most of them are extremely sensitive to outliers. Our approach is based on a simple outlier index. However, instead of robustifying an existing algorithm by some outlier rejection technique we show how this index can be used directly to solve the ICA problem for super-Gaussian sources. The resulting inlier-based ICA (IBICA) is outlier-robust by construction and can be used for standard ICA as well as for overcomplete ICA (i.e. more source signals than observed signals).

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 Dates: 2005-07
 Publication Status: Issued
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 Identifiers: DOI: 10.1002/ima.20037
BibTex Citekey: 6349
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Title: International Journal of Imaging Systems and Technology
  Other : Int. J. Imaging Syst. Technol.
Source Genre: Journal
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Publ. Info: New York : John Wiley & Sons
Pages: - Volume / Issue: 15 (1) Sequence Number: - Start / End Page: 48 - 55 Identifier: ISSN: 0899-9457
CoNE: https://pure.mpg.de/cone/journals/resource/954925561596