aimsalgo 6.0.0
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
45namespace aims
46{
47
48 template<typename Geom, typename Text> class Smoother
49 {
50
51 protected:
52
53 public:
54
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