Supervised Classification

unsupervised classification or automatic interpretation : The operation of a group of multispectral image interpretation functions (such as K-means) that statistically cluster cells into similar collections.

supervised classification develops the rules for assigning reflectance measurements to classes using a "training area", based on input from the user, then applies the rules automatically to the remaining image ...

In an unsupervised classification, the maximum-likelihood classifier uses the cluster means and covariance matrices from the i.

In performing a supervised classification, the representation of a single feature within an image is highly variable as a result of shadowing, terrain, moisture, atmospheric conditions, and sun angle.
Atmospheric Absorption Bands
4.

In supervised classification, a sample of image elements for each land cover class is used to estimate parameters, typically a mean vector and covariance matrix, for input to the classifier.

Now, both 8-bit and 24-bit color image can be classified using R2V's power unsupervised classification function to extract and separate color classes.

S-TCC was based on unsupervised classification of a single multidate data set that contained the six bands from the two dates. ISODATA, an algorithm available in Imagine 8.1, was used in the unsupervised classification.

This collection of tools supports supervised and unsupervised classification and principal component analysis.

See also: Classification, Class, Image, Cover, Area