Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA
This paper introduces an L1-norm-based probabilistic principal component analysis model on 2D data (L1-2DPPCA) based on the assumption of the Laplacian noise model. The Laplacian or L1 density function can be expressed as a superposition of an infinite number of Gaussian distributions. Under this ex...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 24(2015), 12 vom: 20. Dez., Seite 4834-46
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| 1. Verfasser: |
Ju, Fujiao
(VerfasserIn) |
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| Weitere Verfasser: |
Sun, Yanfeng,
Gao, Junbin,
Hu, Yongli,
Yin, Baocai |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2015
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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