opencv3/C++图像滤波实现方式

图像滤波在opencv中可以有多种实现形式

自定义滤波

如使用3×3的掩模：

对图像进行处理.

使用函数filter2D()实现

#include<opencv2/opencv.hpp>
using namespace cv;

int main()
{
 //函数调用filter2D功能
 Mat src,dst;
 src = imread("E:/image/image/daibola.jpg");
 if(!src.data)
 {
  printf("can not load image \n");
  return -1;
 }
 namedWindow("input", CV_WINDOW_AUTOSIZE);
 imshow("input", src);
 src.copyTo(dst);
 Mat kernel = (Mat_<int>(3,3)<<1,1,1,1,1,-1,-1,-1,-1);
 double t = (double)getTickCount();
 filter2D(src, dst, src.depth(), kernel);
 std::cout<<((double)getTickCount()-t)/getTickFrequency()<<std::endl;
 namedWindow("output", CV_WINDOW_AUTOSIZE);
 imshow("output", dst);
 printf("%d",src.channels());
 waitKey();
 return 0;
}

通过像素点操作实现

#include<opencv2/opencv.hpp>
using namespace cv;
int main()
{
 Mat src, dst;
 src = imread("E:/image/image/daibola.jpg");
 CV_Assert(src.depth() == CV_8U);
 if(!src.data)
 {
  printf("can not load image \n");
  return -1;
 }
 namedWindow("input", CV_WINDOW_AUTOSIZE);
 imshow("input",src);
 src.copyTo(dst);
 for(int row = 1; row<(src.rows - 1); row++)
 {
  const uchar* previous = src.ptr<uchar>(row - 1);
  const uchar* current = src.ptr<uchar>(row);
  const uchar* next = src.ptr<uchar>(row + 1);
  uchar* output = dst.ptr<uchar>(row);
  for(int col = src.channels(); col < (src.cols - 1)*src.channels(); col++)
  {
   *output = saturate_cast<uchar>(1 * current[col] + previous[col] - next[col] + current[col - src.channels()] - current[col + src.channels()]);
   output++;
  }
 }
 namedWindow("output", CV_WINDOW_AUTOSIZE);
 imshow("output",dst);
 waitKey();
 return 0;
}

特定形式滤波

常用的有：

blur(src,dst,Size(5,5));均值滤波

GaussianBlur(src,dst,Size(5,5),11,11);高斯滤波

medianBlur(src,dst,5);中值滤波（应对椒盐噪声）

bilateralFilter(src,dst,2,0.5,2,4);双边滤波（保留边缘）

#include<opencv2/opencv.hpp>
using namespace cv;

int main()
{
 Mat src, dst;
 src = imread("E:/image/image/daibola.jpg");
 CV_Assert(src.depth() == CV_8U);
 if(!src.data)
 {
  printf("can not load image \n");
  return -1;
 }
 namedWindow("input", CV_WINDOW_AUTOSIZE);
 imshow("input",src);
 src.copyTo(dst);
 //均值滤波
 blur(src,dst,Size(5,5));
 //中值滤波
 //medianBlur(src,dst,5);

 namedWindow("output", CV_WINDOW_AUTOSIZE);
 imshow("output",dst);

 waitKey();
 return 0;
}

以上这篇opencv3/C++图像滤波实现方式就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持猪先飞。