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00026 #ifndef MLN_LINEAR_GAUSSIAN_1D_HH
00027 # define MLN_LINEAR_GAUSSIAN_1D_HH
00028
00034
00035 #include <mln/core/image/image1d.hh>
00036 #include <mln/linear/gaussian_directional_2d.hh>
00037
00038
00039
00040 namespace mln
00041 {
00042
00043 namespace linear
00044 {
00045
00046
00047 template <typename I>
00048 mln_concrete(I)
00049 gaussian_1d(const Image<I>& input,
00050 double sigma,
00051 const mln_value(I)& bdr);
00052
00053
00054
00055 # ifndef MLN_INCLUDE_ONLY
00056
00057 template <typename I>
00058 inline
00059 mln_concrete(I)
00060 gaussian_1d(const Image<I>& input_,
00061 double sigma,
00062 const mln_value(I)& bdr)
00063 {
00064 trace::entering("linear::gaussian_1d");
00065
00066 typedef mln_site(I) P;
00067 mlc_bool(P::dim == 1)::check();
00068
00069 const I& input = exact(input_);
00070 mln_precondition(input.is_valid());
00071
00072 my::recursivefilter_coef_ coef(1.68f, 3.735f,
00073 1.783f, 1.723f,
00074 -0.6803f, -0.2598f,
00075 0.6318f, 1.997f,
00076 sigma,
00077 my::recursivefilter_coef_::DericheGaussian);
00078
00079 extension::adjust_fill(input, 5 * int(sigma + .50001) + 1, bdr);
00080 mln_concrete(I) output = duplicate(input);
00081
00082 if (sigma < 0.006)
00083 return output;
00084
00085 int
00086 ninds = geom::ninds(input),
00087 b = input.border();
00088
00089 recursivefilter_directional_fastest(output, coef,
00090 point1d(- b),
00091 point1d(ninds - 1 + b),
00092 ninds + 2 * b,
00093 dpoint1d(1),
00094 bdr);
00095
00096 trace::exiting("linear::gaussian_1d");
00097 return output;
00098 }
00099
00100 # endif // ! MLN_INCLUDE_ONLY
00101
00102 }
00103
00104 }
00105
00106
00107 #endif // ! MLN_LINEAR_GAUSSIAN_1D_HH