aimsalgo  5.1.2
Neuroimaging image processing
sixthorderresampler_d.h
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33 
34 
35 #ifndef AIMS_RESAMPLING_SIXTHORDERRESAMPLER_D_H
36 #define AIMS_RESAMPLING_SIXTHORDERRESAMPLER_D_H
37 
39 
40 #include <cmath>
41 
42 namespace aims
43 {
44 
45 template < class T >
47  : SplineResampler< T >()
48 {
49 
50  this->_poles.push_back(
51  -0.488294589303044755130118038883789062112279161239377608394 );
52  this->_poles.push_back(
53  -0.081679271076237512597937765737059080653379610398148178525368 );
54  this->_poles.push_back(
55  -0.00141415180832581775108724397655859252786416905534669851652709 );
56  this->_gain = 2.598975999348577818390170516255374207847876853191217652822;
57 
58 }
59 
60 
61 template < class T >
63 {
64 }
65 
66 
67 template < class T >
69 {
70 
71  return 6;
72 
73 }
74 
75 
76 template < class T >
77 double SixthOrderResampler< T >::getBSplineWeight( int i, double x ) const
78 {
79 
80  x = std::fabs( x - ( double )i );
81  if ( x < 0.5 )
82  {
83 
84  x *= x;
85  return x * ( x * ( 7.0 / 48.0 - x * ( 1.0 / 36.0 ) ) - 77.0 / 192.0 ) +
86  5887.0 / 11520.0;
87 
88  }
89  if ( x < 1.5 )
90  {
91 
92  return x * ( x * ( x * ( x * ( x * ( x * ( 1.0 / 48.0 ) - 7.0 / 48.0 ) +
93  0.328125 ) - 35.0 / 288.0 ) - 91.0 / 256.0 ) - 7.0 / 768.0 ) +
94  7861.0 / 15360.0;
95 
96  }
97  if ( x < 2.5 )
98  {
99 
100  return x * ( x * ( x * ( x * ( x * ( 7.0 / 60.0 - x * ( 1.0 / 120.0 ) ) -
101  0.65625 ) + 133.0 / 72.0 ) - 2.5703125 ) + 1267.0 / 960.0 ) +
102  1379.0 / 7680.0;
103 
104  }
105  if ( x < 3.5 )
106  {
107 
108  x -= 3.5;
109  x *= x * x;
110  return x * x * ( 1.0 / 720.0 );
111 
112  }
113  return 0.0;
114 
115 }
116 
117 } // namespace aims
118 
119 #endif
int getOrder() const CARTO_OVERRIDE
Spline order (1 to 7)
double getBSplineWeight(int i, double x) const CARTO_OVERRIDE
Returns .
B-Spline-based resampling.
std::vector< double > _poles