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Using the Canonical Correlation Analysis Technique for Imaging Dimensionality Reduction in Multisource Land sat Images | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 2, Volume 13, Issue 1, 2013, Pages 1-18 PDF (0 K) | ||
| DOI: 10.33899/iqjoss.2013.075422 | ||
| Abstract | ||
| The Canonical Correlations Analysis technique (CCA) was suggested in the dimensionality reduction images for the multivariate multisource data applied in remote sensing . These techniques transform multivariate multiset data into new orthogonal variables called Canonical Variates (CVs) . This research uses the LANDSAT-5 TM data for the set of multivariate multispectral correlation at fixed points in time . The results show maximum similarity for the low- order canonical variates and minimum similarity for the high- order canonical variates . | ||
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