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<h2>Image processing in GRASS GIS</h2>
<h3>Image data in general</h3>
In GRASS, image data are identical to <a href="rasterintro.html">raster data</a>.
However, a couple of commands are explicitly dedicated to image
processing. The geographic boundaries of the raster/imagery file are
described by the north, south, east, and west fields. These values
describe the lines which bound the map at its edges. These lines do
NOT pass through the center of the grid cells at the edge of the map,
but along the edge of the map itself.
<P>
As a general rule in GRASS:
<ol>
<li> Raster/imagery output maps have their bounds and resolution equal
to those of the current region.
<li> Raster/imagery input maps are automatically cropped/padded and
rescaled (using nearest-neighbor resampling) to match the current
region.
</ol>
<h3>Raster import</h3>
The module <a href="r.in.gdal.html">r.in.gdal</a> offers a common
interface for many different raster and satellite image
formats. Additionally, it also offers options such as on-the-fly
location creation or extension of the default region to match the
extent of the imported raster map. For special cases, other import
modules are available. Always the full map is imported. Imagery data
can be group (e.g. channel-wise) with <a href="i.group.html">i.group</a>.
<P>
For importing scanned maps, the user will need to create a
x,y-location, scan the map in the desired resolution and save it into
an appropriate raster format (e.g. tiff, jpeg, png, pbm) and then use
<a href="r.in.gdal.html">r.in.gdal</a> to import it. Based on
reference points the scanned map can be rectified to obtain geocoded
data.
<h3>Image processing operations</h3>
GRASS raster/imagery map processing is always performed in the current
region settings (see <a href="g.region.html">g.region</a>), i.e. the
current region extent and current raster resolution is used. If the
resolution differs from that of the input raster map(s), on-the-fly
resampling is performed (nearest neighbor resampling). If this is not
desired, the input map(s) has/have to be resampled beforehand with one
of the dedicated modules.
<h3>Geocoding of imagery data</h3>
GRASS is able to geocode raster and image data of various types:
<ul>
<li>unreferenced scanned maps by defining four corner points
(<a href="i.group.html">i.group</a>, <a href="i.target.html">i.target</a>,
<a href="i.points.html">i.points</a>, <a href="i.rectify.html">i.rectify</a>)</li>
<li>unreferenced satellite data from optical and Radar sensors by
defining a certain number of ground control points
(<a href="i.group.html">i.group</a>, <a href="i.target.html">i.target</a>,
<a href="i.points.html">i.points</a>, <a href="i.rectify.html">i.rectify</a>)</li>
<li>orthophoto based on DEM: <a href="i.ortho.photo.html">i.ortho.photo</a></li>
<li>digital handheld camera geocoding: modified procedure for
<a href="i.ortho.photo.html">i.ortho.photo</a></li>
</ul>
<h3>Visualizing (true) color composites</h3>
To quickly combine the first three channels to a near natural color
image, the GRASS command <a href="d.rgb.html">d.rgb</a> can be used or
the graphical GIS manager (<a href="gis.m.html">gis.m</a>). It assigns
each channel to a color which is then mixed while displayed. With a
bit more work of tuning the grey scales of the channels, nearly
perfect colors can be achieved. Channel histograms can be shown with
<a href="d.histogram.html">d.histogram</a>.
<h3>Calculation of vegetation indices</h3>
An example for indices derived from multispectral data is the NDVI
(normalized difference vegetation index). To study the vegetation
status with NDVI, the Red and the Near Infrared channels (NIR) are
taken as used as input for simple map algebra in the GRASS command
<a href="r.mapcalc.html">r.mapcalc</a>
(<tt>ndvi = 1.0 * (nir - red)/(nir + red)</tt>). With
<a href="r.colors.html">r.colors</a> an optimized "ndvi" color table
can be assigned afterward. Also other vegetation indices can be
generated likewise.
<h3>Calibration of thermal channel</h3>
The encoded digital numbers of a thermal infrared channel can be
transformed to degree Celsius (or other temperature units) which
represent the temperature of the observed land surface. This requires
a few algebraic steps with <a href="r.mapcalc.html">r.mapcalc</a>
which are outlined in the literature to apply gain and bias values
from the image metadata.
<h3>Image classification</h3>
Single and multispectral data can be classified to user defined land
use/land cover classes. In case of a single channel, segmentation will
be used.
GRASS supports the following methods:
<ul>
<li> Radiometric classification:
<ul>
<li> Unsupervised classification (<a href="i.cluster.html">i.cluster</A>,
<a href="i.maxlik.html">i.maxlik</A>) using the Maximum Likelihood
classification method</li>
<li> Supervised classification (<a href="i.gensig.html">i.gensig</A>
or <a href="i.class.html">i.class</A>, <a href="i.maxlik.html">i.maxlik</A>)
using the Maximum Likelihood classification method</li>
</ul>
<li> Combined radiometric/geometric (segmentation based) supervised
classification (<A HREF="i.gensigset.html">i.gensigset</A>,
<a href="i.smap.html">i.smap</a>)
</ul>
Kappa statistic can be calculated to validate the results
(<a href="r.kappa.html">r.kappa</a>).
<h3>Image fusion</h3>
In case of using multispectral data, improvements of the resolution
can be gained by merging the panchromatic channel with color
channels. GRASS provides the HIS (<a href="i.rgb.his.html">i.rgb.his</a>,
<a href="i.his.rgb.html">i.his.rgb</a>) and the Brovey transform
(<a href="i.fusion.brovey.html">i.fusion.brovey</a>) methods.
<h3>Time series processing</h3>
GRASS also offers support for time series processing (<a
href="r.series.html">r.series</a>). Statistics can be derived from a
set of coregistered input maps such as multitemporal satellite
data. The common univariate statistics and also linear regression can
be calculated.
<h3>See also</h3>
<ul>
<li>The GRASS 4
<em><A HREF="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
Processing manual</A></EM>
<li><a href=rasterintro.html>Introduction to GRASS 2D raster map processing</a></li>
<li><a href=raster3dintro.html>Introduction to GRASS 3D raster map (voxel) processing</a></li>
<li><a href=vectorintro.html>Introduction to GRASS vector map processing</a></li>
</ul>
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