rolling_normalization.cpp
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29 
31 
32 namespace swri_image_util
33 {
35  max_size_(size),
36  samples_(0)
37  {
38 
39  }
40 
42  {
43 
44  }
45 
46  cv::Mat RollingNormalization::AddSample(const cv::Mat& image)
47  {
48  if (samples_ == 0)
49  {
50  image.convertTo(average_image_, CV_64F, 1.0, 0.0);
51  }
52  else
53  {
54  cv::Mat temp;
55  image.convertTo(temp, CV_64F, 1.0, 0.0);
56  double s = static_cast<double>(samples_);
57  average_image_ = (average_image_ * s + temp) / (s + 1.0);
58  }
59 
60  samples_++;
61  if (samples_ > max_size_)
62  {
64  }
65 
66  cv::Mat mean_image;
67  average_image_.convertTo(mean_image, CV_8U);
68  cv::Mat temp_norm_image;
69 
70  cv::medianBlur(mean_image, temp_norm_image, 25);
71 
72  cv::Mat temp_norm_image2;
73  temp_norm_image.convertTo(temp_norm_image2, CV_32F);
74  double max1 = 0;
75  for (int32_t i = 0; i < temp_norm_image2.rows; i++)
76  {
77  for (int32_t j = 0; j < temp_norm_image2.cols; j++)
78  {
79  if (temp_norm_image2.at<float>(i, j) > max1)
80  {
81  max1 = temp_norm_image2.at<float>(i, j);
82  }
83  }
84  }
85 
86  temp_norm_image2 = temp_norm_image2 * (255.0 / max1);
87 
88  cv::Mat temp_norm_image3;
89  temp_norm_image2.convertTo(temp_norm_image3, CV_8U, 1.0, 0.0);
90 
91 
92  cv::GaussianBlur(temp_norm_image3,
94  cv::Size(15, 15),
95  5,
96  5);
97  return norm_image_;
98  }
99 }
XmlRpcServer s
cv::Mat AddSample(const cv::Mat &image)


swri_image_util
Author(s): Kris Kozak
autogenerated on Tue Apr 6 2021 02:50:39