Hidden image separation from incomplete image mixtures by independent component analysis

Wlodzimierz Kasprzak, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Citations (Scopus)

Abstract

It is known that the independent component analysis (ICA) (also called blind source separation) can be applied only if the number of received signals (sensors) is at least equal to the number of mixed sources, contained in the sensor signals. In this paper an application of the ICA is proposed for hidden (secured) image transmission by communication channels. We assume that only a single image mixture is transmitted. A friendly receiver contains the remaining original sources and therefore it can separate the hidden image of lowest energy. The influence of two nonlossless signal reduction stages, compression by principal component analysis and signal quantization, onto the separation ability is tested. Constraints of the mixing process are discussed that make impossible the hidden image separation without the key images.

Original languageEnglish
Title of host publicationTrack B
Subtitle of host publicationPattern Recognition and Signal Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages394-398
Number of pages5
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - 1996
Externally publishedYes
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: 25 Aug 199629 Aug 1996

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Conference

Conference13th International Conference on Pattern Recognition, ICPR 1996
Country/TerritoryAustria
CityVienna
Period25/08/9629/08/96

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