A.I.M.S algorithms


peronaMalikSmoother.h
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33 
34 
35 #ifndef AIMS_PRIMALSKETCH_PERONAMALIKSMOOTHER_H
36 #define AIMS_PRIMALSKETCH_PERONAMALIKSMOOTHER_H
37 
39 
40 namespace aims
41 {
42 
43  template<class T> class PeronaMalikSmoother
44  : public Smoother<AimsData<T>, AimsData<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 
86  AimsData<T> doSmoothing( const AimsData<T> & ima, int maxiter,
87  bool verbose=false);
88 
89  float dt() {return _dt;}
90  bool optimal() {return true;}
91 
92  };
93 
94 }
95 
96 #endif
AimsData< T > doSmoothing(const AimsData< T > &ima, int maxiter, bool verbose=false)
PeronaMalikSmoother(float dt, float K, float sigma, int cond)