Dimensionality Reduction of Hyperspectral Images by Combination of Non-parametric Weighted Feature Extraction (nwfe) and Modified Neighborhood Preserving Embedding (npe)
نویسندگان
چکیده
This paper combine two conventional feature extraction methods (NWFE&NPE) in a novel framework and present a new semisupervised feature extraction method called Adjusted Semi supervised Discriminant Analysis (ASEDA). The advantage of this method is dominating the Hughes phenomena, automatic selection of unlabelled pixels, extraction of more than L-1(L: number of classes) features and avoidance of singularity or near singularity of within-class scatter matrix. Experimental results on well-known hyperspectral dataset demonstrate that compared to conventional extraction algorithms the overall accuracy of the classification increased. * Corresponding author.
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