ERDAS Imagine: Classification using Minimum Distance Classifier
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7 سال پیش
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This video demonstrates how to
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.
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.
7 سال پیش
در تاریخ 1396/02/04 منتشر شده
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