Unsupervised classification identifies larger number of spectrally-distinct classes than supervised classification.
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In case of unsupervised classification, the computer makes use of algorithms that join similar pixels together based on their similarity with like pixels and dissimilarity to other pixels. This classification is also called clustering and makes use of a general classification scheme. There is no need to have knowledge of the classes beforehand.
Human errors are lesser in unsupervised classification compared to its supervised counterpart. This classification is also very easy and fast to perform.
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due to the special properties and functions , both are not same and unsupervised classification identifies large no.of spectrally distinct classes
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