function that classifies the cell spectral reflectances in imagery
data based on the
spectral signature information generated by either
(GRASS Image Processing Program)
i.maxlik [-q] group=name
i.maxlik is a maximum-likelihood discriminant
analysis classifier. It can be used to perform the second
step in either an unsupervised or a supervised image
Either image classification methods are performed in two
steps. The first step in an unsupervised image
classification is performed by
first step in a supervised classification is executed by
the GRASS program
i.class. In both cases,
the second step in the image classification procedure is
performed by i.maxlik.
In an unsupervised classification, the maximum-likelihood
classifier uses the cluster means and covariance matrices
from the i.cluster
signature file to determine to which category (spectral
class) each cell in the image has the highest probability
of belonging. In a supervised image classification, the
maximum-likelihood classifier uses the region means and
covariance matrices from the spectral signature file
i.class, based on regions
(groups of image pixels) chosen by the user, to determine
to which category each cell in the image has the highest
probability of belonging.
In either case, the raster map layer output by
i.maxlik is a classified image in which each cell
has been assigned to a spectral class (i.e., a category).
The spectral classes (categories) can be related to
specific land cover types on the ground.
The program will run non-interactively if the user
specifies the names of raster map layers, i.e., group and
subgroup names, seed signature file name, result
classification file name, and any combination of
non-required options in the command line, using the form
where each flag and options have the meanings stated below.
Alternatively, the user can simply type i.maxlik
in the command line without program arguments. In this case
the user will be prompted for the program parameter
settings; the program will run foreground.
- Run quietly, without printing program messages to standard output.
- The imagery group
contains the subgroup to be classified.
- The subgroup contains image files, which were used to create
the signature file
in the program i.cluster,
i.gensig to be classified.
- The name of the signatures to be used for the
classification. The signature file contains the cluster and
covariance matrices that were calculated by the GRASS
(or the region means and covariance matrices generated by
i.class, if the
user runs a supervised classification). These spectral
signatures are what determine the categories (classes) to
which image pixels will be assigned during the
- The name of a raster map holds the classification
results. This new raster map layer will contain categories
that can be related to land cover categories on the
- The optional name of a raster map holds the reject
threshold results. This is the result of a chi square test
on each discriminant result at various threshold levels of
confidence to determine at what confidence level each cell
classified (categorized). It is the reject threshold map
layer, and contains one calculated confidence level for
each classified cell in the classified image. One of the
possible uses for this map layer is as a mask, to identify
cells in the classified image that have the lowest
probability of being assigned to the correct class.
The maximum-likelihood classifier assumes that the spectral
signatures for each class (category) in each band file
are normally distributed (i.e., Gaussian in nature).
Algorithms, such as
however, can create signatures that are not valid
distributed (more likely with
If this occurs,
will reject them and display a warning message.
This program runs interactively if the user types
i.maxlik only. If the user types i.maxlik
along with all required options, it will overwrite the
classified raster map without prompting if this map
GRASS Tutorial: Image Pro
U.S.Army Construction Engineering
University of Illinois at Urbana-Champaign,