answer_19.cpp

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <math.h>


// BGR -> Gray
cv::Mat BGR2GRAY(cv::Mat img){
  // get height and width
  int width = img.cols;
  int height = img.rows;

  // prepare output
  cv::Mat out = cv::Mat::zeros(height, width, CV_8UC1);

  // each y, x
  for (int y = 0; y < height; y++){
    for (int x = 0; x < width; x++){
      // BGR -> Gray
      out.at<uchar>(y, x) = 0.2126 * (float)img.at<cv::Vec3b>(y, x)[2] \
        + 0.7152 * (float)img.at<cv::Vec3b>(y, x)[1] \
        + 0.0722 * (float)img.at<cv::Vec3b>(y, x)[0];
    }
  }
  return out;
}

// LoG filter
cv::Mat LoG_filter(cv::Mat img, int kernel_size, double sigma){
  int height = img.rows;
  int width = img.cols;
  int channel = img.channels();

  // prepare output
  cv::Mat out = cv::Mat::zeros(height, width, CV_8UC1);

  // prepare kernel
  int pad = floor(kernel_size / 2);
  double kernel[kernel_size][kernel_size];
  double kernel_sum = 0;
  double _x, _y;
  for (int y = 0; y < kernel_size; y++){
    for (int x = 0; x < kernel_size; x++){
      _y = y - pad;
      _x = x - pad; 
      kernel[y][x] = (_x * _x + _y * _y - sigma * sigma) / (2 * M_PI * pow(sigma, 6)) * exp( - (_x * _x + _y * _y) / (2 * sigma * sigma));
      kernel_sum += kernel[y][x];
    }
  }
  for (int y = 0; y < kernel_size; y++){
    for (int x = 0; x < kernel_size; x++){
      kernel[y][x] /= kernel_sum;
    }
  }

  double v = 0;

  // filtering  
  for (int y = 0; y < height; y++){
    for (int x = 0; x < width; x++){
      v = 0;
      for (int dy = -pad; dy < pad + 1; dy++){
        for (int dx = -pad; dx < pad + 1; dx++){
          if (((y + dy) >= 0) && (( x + dx) >= 0) && ((y + dy) < height) && ((x + dx) < width)){
            v += img.at<uchar>(y + dy, x + dx) * kernel[dy + pad][dx + pad];
          }
        }
      }
      v = fmax(v, 0);
      v = fmin(v, 255);
      out.at<uchar>(y, x) = (uchar)v;
    }
  }
  return out;
}

int main(int argc, const char* argv[]){
  // read image
  cv::Mat img = cv::imread("imori_noise.jpg", cv::IMREAD_COLOR);

  // BGR -> Gray
  cv::Mat gray = BGR2GRAY(img);

  // LoG filter
  cv::Mat out = LoG_filter(gray, 5, 3);
  
  //cv::imwrite("out.jpg", out);
  cv::imshow("answer", out);
  cv::waitKey(0);
  cv::destroyAllWindows();
 
  return 0;
}