mimas: gauss.h Source File

00001 #ifndef GAUSS_H
00002 #define GAUSS_H
00003 
00004 #include <boost/multi_array.hpp>
00005 #include <cassert>
00006 #include <cmath>
00007 #include <deque>
00008 #include "image.h"
00009 #include "image_conv.h"
00010 #include "image_op.h"
00011 
00012 namespace mimas {
00013 
00037 template< typename T >
00038 std::deque< T > gaussBlurFilter( T sigma, T maxError = (T)( 1.0 / 256.0 ) );
00039 
00046 template< typename T >
00047 boost::multi_array< T, 2 > gaussBlur
00048   ( const boost::const_multi_array_ref< T, 2 > &x, T sigma, T maxError );
00049 
00056 template< typename T >
00057 image< T > gaussBlur( const image< T > &x, T sigma,
00058                       T maxError = (T)( 1.0 / 256.0 ) )
00059 {
00060   boost::const_multi_array_ref< T, 2 > data
00061     ( x.rawData(), boost::extents[ x.getHeight() ][ x.getWidth() ] );
00062   image< T > retVal; retVal.init( x.getWidth(), x.getHeight() );
00063   boost::multi_array_ref< T, 2 >
00064     ( retVal.rawData(),
00065       boost::extents[ retVal.getHeight() ][ retVal.getWidth() ] ) =
00066     gaussBlur< T >( data, sigma, maxError );
00067   return retVal;
00068 }
00069 
00081 template< typename T >
00082 std::deque< T > gaussGradientFilter( T sigma,
00083                                      T maxError = (T)( 1.0 / 256.0 ) );
00084 
00091 template< typename T >
00092 boost::multi_array< T, 2 > gaussGradientX
00093   ( const boost::const_multi_array_ref< T, 2 > &x, T sigma, T maxError );
00094 
00101 template< typename T >
00102 image< T > gaussGradientX( const image< T > &x, T sigma,
00103                            T maxError = (T)( 1.0 / 256.0 ) );
00104 
00111 template< typename T >
00112 boost::multi_array< T, 2 > gaussGradientY
00113   ( const boost::const_multi_array_ref< T, 2 > &x, T sigma, T maxError );
00114 
00121 template< typename T >
00122 image< T > gaussGradientY( const image< T > &x, T sigma,
00123                            T maxError = (T)( 1.0 / 256.0 ) );
00124 
00131 template< typename T >
00132 image< T > gaussGradientSqr( const image< T > &im, T sigma,
00133                              T maxError = (T)( 1.0 / 256.0 ) )
00134 {
00135   image< T >
00136     gradX( gaussGradientX( im, sigma, maxError ) ),
00137     gradY( gaussGradientY( im, sigma, maxError ) );
00138   return sumSquares( gradX, gradY );
00139 }
00140 
00147 template< typename T >
00148 image< T > gaussGradientNorm( const image< T > &im, T sigma,
00149                               T maxError = (T)( 1.0 / 256.0 ) )
00150 {
00151   return squareRoot( gaussGradientSqr( im, sigma, maxError ) );
00152 }
00153 
00155 
00156 };
00157 
00158 #include "gauss.tcc"
00159 
00160 #endif