aimsalgo  5.1.2
Neuroimaging image processing
smoother.h
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33 
34 
35 // REM about scale (t) and variance (s):
36 // When using a Gaussian filtering we use the following convention:
37 // t=s^2.
38 // It corresponds to the heat equation: dI/dt=0.5*Laplacian(I)
39 
40 #ifndef AIMS_PRIMALSKETCH_SMOOTHER_H
41 #define AIMS_PRIMALSKETCH_SMOOTHER_H
42 
44 
45 namespace aims
46 {
47 
48  template<typename Geom, typename Text> class Smoother
49  {
50 
51  protected:
52 
53  public:
54 
55  Smoother() {}
56  virtual ~Smoother() {}
57  virtual Text doSmoothing(const Text & ima, int maxiter, bool verbose=false)=0; // smooth operator...
58  virtual float dt() {return 0.0;} //smooooth operatooor... // virtuel pur
59  virtual bool optimal() {return false;} // optimal smoothing method:
60  // 0 -> from original image (ex: convolution)
61  // 1 -> from previous scale (ex: diffusion)
62  };
63 
64 }
65 #endif
virtual bool optimal()
Definition: smoother.h:59
virtual Text doSmoothing(const Text &ima, int maxiter, bool verbose=false)=0
virtual ~Smoother()
Definition: smoother.h:56
virtual float dt()
Definition: smoother.h:58