Hidden image separation from incomplete image mixtures by independent component analysis

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 h...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 2; pp. 394 - 398 vol.2
Main Authors Kasprzak, W., Cichocki, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Communication channels
Decoding
Image coding
Independent component analysis
Laboratories
Neural networks
Noise reduction
Principal component analysis
Quantization
Testing
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ISBN9780818672828
081867282X
ISSN1051-4651
DOI10.1109/ICPR.1996.546855

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Summary: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.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.546855