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Unsupervised Classification of Aerial Images Based on the Otsu’s Method 173
2. Materials and methods
2.1 Study area
In the present investigation 16 color aerial photographs in digital format were used, owned
by the Institute of Geography of the Autonomous University of Mexico, taken in October
1997. The photographs correspond to the catchments of the river La Sabana, Guerrero, with
spatial resolution of 1:19500, and three-band spectral resolution visible and radiometric
resolution RGB from 0 to 255 levels. As an example, Fig. 1 displays a representative image of
the set of images analyzed in this work. As we can see it contains several textures which
must be classified as belonging to a cluster.
Fig. 1. Land cover images in RGB color model
2.2 Classifier based on the theory of the Otsu’s method
2.2.1 Brief description of the Otsu’s method
Otsu’s method [10], one of the most widely used thresholding techniques in image analysis,
has showed great success in image enhancement and segmentation. As mentioned before, it
is an automatic thresholding strategy; we exploit the automatic capability for designing the
unsupervised classification strategy justifying its choice.
This research sought the optimal threshold (single or multiple) for each of the spectral bands
of the color image by applying the algorithm modified [27, 28]:
The number of pixels with gray level i is denoted f i giving a probability of gray level i in an
image of
f
i pi N
Then, the probability distributions for each class is
(1)