Point Cloud Library (PCL) 1.15.0
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convolution.hpp
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37
38#pragma once
39
40#include <pcl/2d/convolution.h>
41
42namespace pcl {
43
44template <typename PointT>
45void
47{
48 int input_row = 0;
49 int input_col = 0;
50 // default boundary option : zero padding
51 output = *input_;
52
53 int iw = static_cast<int>(input_->width), ih = static_cast<int>(input_->height),
54 kw = static_cast<int>(kernel_.width), kh = static_cast<int>(kernel_.height);
55 switch (boundary_options_) {
56 default:
57 case BOUNDARY_OPTION_CLAMP: {
58 for (int i = 0; i < ih; i++) {
59 for (int j = 0; j < iw; j++) {
60 float intensity = 0;
61 for (int k = 0; k < kh; k++) {
62 for (int l = 0; l < kw; l++) {
63 int ikkh = i + k - kh / 2, jlkw = j + l - kw / 2;
64 if (ikkh < 0)
65 input_row = 0;
66 else if (ikkh >= ih)
67 input_row = ih - 1;
68 else
69 input_row = ikkh;
70
71 if (jlkw < 0)
72 input_col = 0;
73 else if (jlkw >= iw)
74 input_col = iw - 1;
75 else
76 input_col = jlkw;
77
78 intensity +=
79 kernel_(l, k).intensity * (*input_)(input_col, input_row).intensity;
80 }
81 }
82 output(j, i).intensity = intensity;
83 }
84 }
85 break;
86 }
87
88 case BOUNDARY_OPTION_MIRROR: {
89 for (int i = 0; i < ih; i++) {
90 for (int j = 0; j < iw; j++) {
91 float intensity = 0;
92 for (int k = 0; k < kh; k++) {
93 for (int l = 0; l < kw; l++) {
94 int ikkh = i + k - kh / 2, jlkw = j + l - kw / 2;
95 if (ikkh < 0)
96 input_row = -ikkh - 1;
97 else if (ikkh >= ih)
98 input_row = 2 * ih - 1 - ikkh;
99 else
100 input_row = ikkh;
101
102 if (jlkw < 0)
103 input_col = -jlkw - 1;
104 else if (jlkw >= iw)
105 input_col = 2 * iw - 1 - jlkw;
106 else
107 input_col = jlkw;
108
109 intensity +=
110 kernel_(l, k).intensity * ((*input_)(input_col, input_row).intensity);
111 }
112 }
113 output(j, i).intensity = intensity;
114 }
115 }
116 break;
117 }
118
119 case BOUNDARY_OPTION_ZERO_PADDING: {
120 for (int i = 0; i < ih; i++) {
121 for (int j = 0; j < iw; j++) {
122 float intensity = 0;
123 for (int k = 0; k < kh; k++) {
124 for (int l = 0; l < kw; l++) {
125 int ikkh = i + k - kh / 2, jlkw = j + l - kw / 2;
126 if (ikkh < 0 || ikkh >= ih || jlkw < 0 || jlkw >= iw)
127 continue;
128 intensity += kernel_(l, k).intensity * ((*input_)(jlkw, ikkh).intensity);
129 }
131 output(j, i).intensity = intensity;
132 }
133 }
134 break;
135 }
136 } // switch
137}
138} // namespace pcl
void filter(pcl::PointCloud< PointT > &output)
Performs 2D convolution of the input point cloud with the kernel.
PointCloud represents the base class in PCL for storing collections of 3D points.