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In supervised classification of remotely sensed imagery the
analysts require a plenty of time for generating the representative
signatures of the possible land-cover classes present in the image.
Although the notion of picking a large number of input signatures
leads to more efficient results but in most of the situations the
time is an important factor. To save the lavish time, besides to
obtain the reliable results, is the requirement of most of the
analysts. In this study the results of supervised classification
are used as reference for checking the reliability of the results
obtained with guided clustering technique as this technique is
based on ground truth data and the ancillary information.
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