aimsalgo 6.0.0
Neuroimaging image processing
peronaMalikSmoother.h
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33
34
35#ifndef AIMS_PRIMALSKETCH_PERONAMALIKSMOOTHER_H
36#define AIMS_PRIMALSKETCH_PERONAMALIKSMOOTHER_H
37
39
40namespace aims
41{
42
43 template<class T> class PeronaMalikSmoother
44 : public Smoother<carto::VolumeRef<T>, carto::VolumeRef<T> >
45 {
46
47 private:
48
49 float _K; // control of the gradient - proportion of gradients which are NOT edges - generally around 0.98
50 float _gradK; // the actual gradient bound, computed from K and the image to be processed
51 float _sigma; // regularisation parameter (i.e. smoothing of the gradient)
52 float _dt;
53
54 int _conductance; // vaut 1, ou 2, ou autrre si on rajoute des fonctions de conductance
55
56 inline float conductance(float x)
57 {
58 switch (_conductance)
59 {
60 case 1: return(conductance1(x));
61 case 2: return(conductance2(x));
62 default : exit(EXIT_FAILURE);
63 }
64 }
65
66 inline float conductance1(float x)
67 { return (1.0/float(1.0+(x*x)/(_gradK*_gradK))); }
68 inline float conductance2(float x)
69 { return (exp(-(x*x)/(_gradK*_gradK))); }
70
71 void SetDt(float dt)
72 {
73 if (dt<=0.25) _dt=dt;
74 else
75 {
76 std::cerr << "Diffusion Smoother : dt must be <= 0.25" << std::endl;
77 exit(EXIT_FAILURE);
78 }
79 }
80
81 public:
82
83 PeronaMalikSmoother(float dt, float K, float sigma, int cond)
84 : _K(K), _sigma(sigma), _conductance(cond) {SetDt(dt);}
85
87 int maxiter, bool verbose=false);
88
89 float dt() {return _dt;}
90 bool optimal() {return true;}
91
92 };
93
94}
95
96#endif
carto::VolumeRef< T > doSmoothing(const carto::VolumeRef< T > &ima, int maxiter, bool verbose=false)
PeronaMalikSmoother(float dt, float K, float sigma, int cond)