[GRASS-SVN] r60963 - grass/branches/releasebranch_6_4/imagery/i.gensigset
svn_grass at osgeo.org
svn_grass at osgeo.org
Wed Jun 25 05:20:14 PDT 2014
Author: neteler
Date: 2014-06-25 05:20:14 -0700 (Wed, 25 Jun 2014)
New Revision: 60963
Modified:
grass/branches/releasebranch_6_4/imagery/i.gensigset/description.html
Log:
i.gensigset manual: explain 'Unreliable clustering' warning; HTML cosmetics
Modified: grass/branches/releasebranch_6_4/imagery/i.gensigset/description.html
===================================================================
--- grass/branches/releasebranch_6_4/imagery/i.gensigset/description.html 2014-06-25 12:19:36 UTC (rev 60962)
+++ grass/branches/releasebranch_6_4/imagery/i.gensigset/description.html 2014-06-25 12:20:14 UTC (rev 60963)
@@ -1,9 +1,7 @@
<h2>DESCRIPTION</h2>
-
<em>i.gensigset</em>
is a non-interactive method for generating input into
-
<em><a href="i.smap.html">i.smap</a>.</em>
It is used as the first pass in the a two-pass
@@ -13,12 +11,10 @@
extract spectral signatures from an image based on the
classification of the pixels in the training map and make
these signatures available to
-
<em><a href="i.smap.html">i.smap</a>.</em>
<p>
-
The user would then execute the GRASS program <em>
<a href="i.smap.html">i.smap</a></em> to create the
final classified map.
@@ -33,9 +29,7 @@
<dd>ground truth training map
-
<p>
-
This raster layer, supplied as input by the user, has some
of its pixels already classified, and the rest (probably
most) of the pixels unclassified. Classified means that
@@ -43,7 +37,6 @@
the pixel has a zero value.
<p>
-
This map must be prepared by the user in advance.
The user must use
@@ -59,9 +52,7 @@
representative
of the classes in the image.
-
<p>
-
At present, there is no fully-interactive tool specifically
designed for producing this layer.
@@ -70,7 +61,6 @@
<dd>imagery group
<p>
-
This is the name of the group that contains the band files
which comprise the image to be analyzed. The
@@ -80,14 +70,12 @@
comprise an image.
<p>
-
<dt><b>subgroup=</b><em>name</em>
<dd>subgroup containing image files
<p>
-
This names the subgroup within the group that selects a
subset of the bands to be analyzed. The
@@ -103,7 +91,6 @@
<dd>resultant signature file
<p>
-
This is the resultant signature file (containing the means
and covariance matrices) for each class in the training map
that is associated with the band files in the subgroup
@@ -111,17 +98,14 @@
<p>
-
<dt><b>maxsig=</b><em>value</em>
<dd>maximum number of sub-signatures in any class
<br>
-
default: 10
<p>
-
The spectral signatures which are produced by this program
are "mixed" signatures (see <a href="#notes">NOTES</a>).
Each signature contains one or more subsignatures
@@ -130,7 +114,6 @@
number to a minimal number of subclasses which are
spectrally distinct. The user has the option to set this
starting value with this option.
-
</dl>
@@ -141,7 +124,6 @@
names of these maps and files.
<p>
-
It should be noted that interactive mode here only means
interactive prompting for maps and files. It does not mean
visualization of the signatures that result from the
@@ -149,9 +131,8 @@
<p>
+<A NAME="notes"></a><h2>NOTES</h2>
-<A NAME="notes"><h2>NOTES</h2></a>
-
The algorithm in <em>i.gensigset</em> determines the
parameters of a spectral class model known as a Gaussian
mixture distribution. The parameters are estimated using
@@ -162,7 +143,6 @@
of the multispectral image.
<p>
-
The Gaussian mixture class is a useful model because it can
be used to describe the behavior of an information class
which contains pixels with a variety of distinct spectral
@@ -176,7 +156,6 @@
<p>
-
The objective of mixture classes is to improve segmentation
performance by modeling each information class as a
probabilistic mixture with a variety of subclasses. The
@@ -190,7 +169,6 @@
<p>
-
This clustering algorithm estimates both the number of
distinct subclasses in each class, and the spectral mean
and covariance for each subclass. The number of subclasses
@@ -204,61 +182,60 @@
expectation maximization (EM) algorithm
[<a href="#dempster77">2</a>,<a href="#redner84">3</a>].
+<h2>WARNINGS</h2>
-<h2>REFERENCES</h2>
+If warnings like this occur, reducing the remaining classes to 0:
-<ol>
+<div class="code"><pre>
+...
+WARNING: Removed a singular subsignature number 1 (4 remain)
+WARNING: Removed a singular subsignature number 1 (3 remain)
+WARNING: Removed a singular subsignature number 1 (2 remain)
+WARNING: Removed a singular subsignature number 1 (1 remain)
+WARNING: Unreliable clustering. Try a smaller initial number of clusters
+WARNING: Removed a singular subsignature number 1 (-1 remain)
+WARNING: Unreliable clustering. Try a smaller initial number of clusters
+Number of subclasses is 0
+</pre></div>
-<li><A NAME="rissanen83">J. Rissanen,</a>
-"A Universal Prior for Integers and Estimation by Minimum
-Description Length,"
-<em>Annals of Statistics,</em>
-vol. 11, no. 2, pp. 417-431, 1983.
+then the user should check for:
+<ul>
+<li>the range of the input data should be between 0 and 100 or 255 but not
+ between 0.0 and 1.0 (<em>r.info</em> and <em>r.univar</em> show the range)</li>
+<li>the training areas need to contain a sufficient amount of pixels</li>
+</ul>
+<h2>REFERENCES</h2>
+
+<ul>
+<li><A NAME="rissanen83">J. Rissanen,</a>
+"A Universal Prior for Integers and Estimation by Minimum Description Length,"
+<em>Annals of Statistics,</em> vol. 11, no. 2, pp. 417-431, 1983.
<li><A NAME="dempster77">A. Dempster, N. Laird and D. Rubin,</a>
"Maximum Likelihood from Incomplete Data via the EM Algorithm,"
-<em>J. Roy. Statist. Soc. B,</em>
-vol. 39, no. 1, pp. 1-38, 1977.
-
+<em>J. Roy. Statist. Soc. B,</em> vol. 39, no. 1, pp. 1-38, 1977.
<li><A NAME="redner84">E. Redner and H. Walker,</a>
"Mixture Densities, Maximum Likelihood and the EM Algorithm,"
-<em>SIAM Review,</em>
-vol. 26, no. 2, April 1984.
+<em>SIAM Review,</em> vol. 26, no. 2, April 1984.
+</ul>
-</ol>
-
<h2>SEE ALSO</h2>
-<em><a href="i.group.html">i.group</a></em>
-for creating groups and subgroups
+<em>
+<a href="i.group.html">i.group</a>,
+<a href="i.smap.html">i.smap</a>,
+<a href="r.info.html">r.info</a>,
+<a href="r.univar.html">r.univar</a>,
+<a href="v.digit.html">v.digit</a>
+</em>
-
-<p>
-
-<em><a href="v.digit.html">v.digit</a></em>
-and
-<em><a href="r.digit.html">r.digit</a></em>
-for interactively creating the training map.
-
-
-<p>
-
-<em><a href="i.smap.html">i.smap</a></em>
-for creating a final classification layer from the signatures
-generated by <em>i.gensigset.</em>
-
-
<h2>AUTHORS</h2>
Charles Bouman,
-School of
-Electrical Engineering,
-Purdue University
+School of Electrical Engineering, Purdue University
<br>
-
Michael Shapiro,
-U.S.Army Construction Engineering
-Research Laboratory
+U.S.Army Construction Engineering Research Laboratory
<p><i>Last changed: $Date$</i>
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