<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"> <html><head><meta name="robots" content="noindex"> <meta http-equiv="Content-Type" content="text/html;charset=iso-8859-1"> <title>ITK: Markov Random Field-based Filters</title> <link href="DoxygenStyle.css" rel="stylesheet" type="text/css"> </head><body bgcolor="#ffffff"> <!-- Section customized for INSIGHT : Tue Jul 17 01:02:45 2001 --> <center> <a href="index.html" class="qindex">Main Page</a> <a href="modules.html" class="qindex">Groups</a> <a href="namespaces.html" class="qindex">Namespace List</a> <a href="hierarchy.html" class="qindex">Class Hierarchy</a> <a href="classes.html" class="qindex">Alphabetical List</a> <a href="annotated.html" class="qindex">Compound List</a> <a href="files.html" class="qindex">File List</a> <a href="namespacemembers.html" class="qindex">Namespace Members</a> <a href="functions.html" class="qindex">Compound Members</a> <a href="globals.html" class="qindex">File Members</a> <a href="pages.html" class="qindex">Concepts</a></center> <!-- Generated by Doxygen 1.5.9 --> <div class="contents"> <h1>Markov Random Field-based Filters<br> <small> [<a class="el" href="group__RegionBasedSegmentation.html">Region-Based Segmentation Filters</a>]</small> </h1> <p> <div class="dynheader"> Collaboration diagram for Markov Random Field-based Filters:</div> <div class="dynsection"> <center><table><tr><td><img src="group__MRFFilters.png" border="0" alt="" usemap="#group____MRFFilters_map"> <map name="group____MRFFilters_map"> <area shape="rect" id="node2" href="group__RegionBasedSegmentation.html" title="Region-Based Segmentation Filters" alt="" coords="7,5,265,35"></map></td></tr></table></center> </div> <table border="0" cellpadding="0" cellspacing="0"> <tr><td></td></tr> <tr><td colspan="2"><br><h2>Classes</h2></td></tr> <tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="classitk_1_1MRFImageFilter.html">itk::MRFImageFilter< TInputImage, TClassifiedImage ></a></td></tr> <tr><td class="mdescLeft"> </td><td class="mdescRight">Implementation of a labeller object that uses Markov Random Fields to classify pixels in an image data set. <a href="classitk_1_1MRFImageFilter.html#_details">More...</a><br></td></tr> <tr><td class="memItemLeft" nowrap align="right" valign="top">class </td><td class="memItemRight" valign="bottom"><a class="el" href="classitk_1_1RGBGibbsPriorFilter.html">itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage ></a></td></tr> <tr><td class="mdescLeft"> </td><td class="mdescRight"><a class="el" href="classitk_1_1RGBGibbsPriorFilter.html" title="RGBGibbsPriorFilter applies Gibbs Prior model for the segmentation of MRF images...">RGBGibbsPriorFilter</a> applies Gibbs Prior model for the segmentation of MRF images. The core of the method is based on the minimization of a Gibbsian energy function. This energy function f can be divided into three part: f = f_1 + f_2 + f_3; f_1 is related to the object homogeneity, f_2 is related to the boundary smoothness, f_3 is related to the constraint of the observation (or the noise model). The two force components f_1 and f_3 are minimized by the GradientEnergy method while f_2 is minized by the GibbsTotalEnergy method. <a href="classitk_1_1RGBGibbsPriorFilter.html#_details">More...</a><br></td></tr> </table> <hr><a name="_details"></a><h2>Detailed Description</h2> Markov Random Field (MRF)-based Filters assume that the segmented image is Markovian in nature, i.e., adjacent pixels are likely to be of the same class. These methods typically combine intensity-based Filters with MRF prior models also known as Gibbs prior models. </div> <hr><address><small> Generated at Fri May 8 00:43:00 2009 for ITK by <a href="http://www.stack.nl/~dimitri/doxygen/index.html"> <img src="http://www.stack.nl/~dimitri/doxygen/doxygen.png" alt="doxygen" align="middle" border=0 width=110 height=53> </a> 1.5.9 written by <a href="mailto:dimitri@stack.nl">Dimitri van Heesch</a>, © 1997-2000</small></address> </body> </html>
distrib
>
Mandriva
>
2010.0
>
i586
>
media
>
contrib-release
>
by-pkgid
>
d5e74628f0e673bb8680aebce32b2c04
>
files
>
12387
