Classification
Any technique whereby data are grouped into a smaller number of more general integer
categories is known as a classification. In remote sensing, a classification is a procedure
whereby data cells are assigned to one of a broad group of landcover classes according to
the nature of the specific reflectances found at that place.
For classifying an image press reclass button in the IDRISI menu bar or write reclass in
the operation search/query.
From the image Band_04 if we want to extract water bodies then we have to find the
range of the DN values which belongs to water first. Then we have to assign classes in
the reclass tool.
If we put this values in the reclass tool then we will get a image where the DN values of
the Pixels belonging to water will be 1 and all other pixels will have the DN value 0.
For multiple classes we have to assign pixels several times like for single class.
If we perform this operation then we will have several classes. You can put as much class
as you want in this query. These are supervised classification techniques. For supervised
classification image histogram is very important. Because it tells about the number of
classes.
In unsupervised classification we only say the number of desired classes. The ranges of
the DN values are not fixed by us the software itself fixes it. For unsupervised
classification we will use isoclust tool. Here we need to define how many bands we want
to use for classification.
Then we have to define the number of desired classes. Through looking at the histogram
of the image. Once the class is defined then we need to press OK. The classification is
done. We have to remember that unsupervised classification is not a good classification
technique. Because here we have greater chances of error.