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ERDAS Imagine: Classification using Minimum Distance Classifier

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This video demonstrates how to perform image classification using Minimum Distance classifier in ERDAS Imagine.

The minimum distance classifier (MDC) is an example of a commonly used ‘conventional’ classifier. The minimum distance classifier is used to classify unknown image data to classes which minimize the distance between the image data and the class in multi-feature space. The distance is defined as an index of similarity so that the minimum distance is identical to the maximum similarity.

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