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convolve_2x1d.hh
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25 
26 #ifndef MLN_LINEAR_CONVOLVE_2X1D_HH
27 # define MLN_LINEAR_CONVOLVE_2X1D_HH
28 
32 
33 # include <mln/linear/convolve_directional.hh>
34 # include <mln/extension/adjust.hh>
35 # include <mln/util/max.hh>
36 
37 
38 
39 namespace mln
40 {
41 
42  namespace linear
43  {
44 
53  template <typename I,
54  typename W, unsigned Sh, unsigned Sv>
55  mln_ch_convolve(I, W)
56  convolve_2x1d(const Image<I>& input,
57  W (&horizontal_weights)[Sh],
58  W (& vertical_weights)[Sv]);
59 
60 
61 # ifndef MLN_INCLUDE_ONLY
62 
63  template <typename I,
64  typename W, unsigned Sh, unsigned Sv>
65  mln_ch_convolve(I, W)
66  convolve_2x1d(const Image<I>& input,
67  W (&horizontal_weights)[Sh],
68  W (& vertical_weights)[Sv])
69  {
70  trace::entering("linear::convolve_2x1d");
71 
72  mlc_bool(Sh % 2 == 1)::check();
73  mlc_bool(Sv % 2 == 1)::check();
74 
75  mln_precondition(exact(input).is_valid());
76 
77  extension::adjust(input, util::max(Sh / 2, Sv / 2));
78 
79  mln_ch_convolve(I, W) tmp, output;
80  // Horizontal kernel so columns (index 1) are varying.
81  tmp = linear::convolve_directional(input, 1, horizontal_weights);
82  output = linear::convolve_directional( tmp, 0, vertical_weights);
83 
84  trace::exiting("linear::convolve_2x1d");
85  return output;
86  }
87 
88 # endif // ! MLN_INCLUDE_ONLY
89 
90  } // end of namespace mln::linear
91 
92 } // end of namespace mln
93 
94 
95 #endif // ! MLN_LINEAR_CONVOLVE_2X1D_HH