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Found 4 papers, 0 papers with code
NPSA: Nonorthogonal Principal Skewness Analysis
Principal skewness analysis (PSA) has been introduced for feature extraction in hyperspectral imagery.
Probabilistic graphical model based approach for water mapping using GaoFen-2 (GF-2) high resolution imagery and Landsat 8 time series
Difficulties of water mapping on high resolution data includes: 1) misclassification between water and shadows or other low-reflectance ground objects, which is mostly caused by the spectral similarity within the given band range; 2) small water bodies with size smaller than the spatial resolution of MS image.
An automatic bad band preremoval algorithm for hyperspectral imagery
As an example, for the matched filter (MF), which is the most widely used target detection method for hyperspectral data, we present an automatic MF-based algorithm for bad band identification.
Clustering by connection center evolution
Inappropriate scale usually leads to unreasonable cluster centers and thus unreasonable results.
