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脚本之家。
