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AN EFFICIENT INITIALIZATION METHOD FOR K-MEANS CLUSTERING OF HYPERSPECTRAL DATA
K-means Clustering Initialization methods Unmixing MVES Hyperspectral data
2014/12/1
K-means is definitely the most frequently used partitional clustering algorithm in the remote sensing community. Unfortunately due to its gradient decent nature, this algorithm is highly sensitive to ...
Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis
Change Detection principal component analysis fuzzy c-means clustering image differencing remote sensing bi-temporal satellite images
2014/4/22
Change detection analyze means that according to observations made in different times, the process of defining the change detection occurring in nature or in the state of any objects or the ability of...
