Image processing - Image classification
3 important questions on Image processing - Image classification
Difference supervised and unsupervised classification?
Supervised- the analyst identifies the homogeneous representative samples of the different surface cover types of interest (training areas, references for the program) (with knowledge of the area). The categorisation is supervised. Unsupervised - spectral classes are grouped first and are then matched by the analyst to information classes.
What are features of a pixel?
Digital pixel values from different spectral bands. Pixels have their own image space.
Classification algorithms - give four decision rules.
1. The minimum distance to means classification the centre point of each cluster is determined, then the distance to these are calculated, the point is assigned to the nearest cluster.
2. The 'k'-nearest neighbours. k points per cluster are selected.
3. maximum likelihood classification, elipses are drawn about the mean.
4. Parallelepiped. Rectangular areas.
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