aimsalgo  5.0.5
Neuroimaging image processing
g2dsmooth.h
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33 
34 
35 #ifndef AIMS_SIGNALFILTER_G2DSMOOTH_H
36 #define AIMS_SIGNALFILTER_G2DSMOOTH_H
37 
41 
42 
43 template< class T >
45 {
46 public:
47 
48  Gaussian2DSmoothing( float sx=1.0f, float sy=1.0f );
49  virtual ~Gaussian2DSmoothing() { }
50 
51  AimsData< T > doit( const AimsData<T>& );
52 
53 private:
54 
55  float sigx;
56  float sigy;
57 };
58 
59 
60 template< class T > inline
62  : sigx( sx ), sigy( sy )
63 {
64  ASSERT( sigx >= 0.1f && sigx <= 100.0f );
65  ASSERT( sigy >= 0.1f && sigy <= 100.0f );
66 }
67 
68 
69 template< class T > inline
71 {
72  float sx = sigx / data.sizeX();
73  float sy = sigy / data.sizeY();
74 
77  dataF( data.dimX(), data.dimY(), data.dimZ(), data.dimT() );
78  dataF.setSizeX(data.sizeX());
79  dataF.setSizeY(data.sizeY());
80  dataF.setSizeZ(data.sizeZ());
81  conv.convert( data, dataF );
82 
83  GaussianLines glin;
84  glin.doit( dataF, GCoef( sx ) );
85 
86  GaussianColumns gcol;
87  gcol.doit( dataF, GCoef( sy ) );
88 
90  AimsData<T> data3( data.dimX(), data.dimY(), data.dimZ(), data.dimT() );
91  conv2.convert( dataF, data3 );
92  return data3;
93 }
94 
95 #endif
void doit(AimsData< float > &)
int dimZ() const
float sizeZ() const
int dimY() const
virtual ~Gaussian2DSmoothing()
Definition: g2dsmooth.h:49
virtual void convert(const INP &in, OUTP &out) const
void setSizeX(float sizex)
float sizeX() const
Gaussian2DSmoothing(float sx=1.0f, float sy=1.0f)
Definition: g2dsmooth.h:61
Definition: gcoef.h:41
void doit(AimsData< float > &)
float sizeY() const
AimsData< T > doit(const AimsData< T > &)
Definition: g2dsmooth.h:70
int dimT() const
#define ASSERT(EX)
int dimX() const