C++ 如何用中值滤波算法去除椒盐噪声
我用c++编写了一个代码,使用CImg库在图像中添加噪声。现在我想加载带有噪声的图像,并使用中值滤波算法去除图像中的噪声。 下面是我的代码C++ 如何用中值滤波算法去除椒盐噪声,c++,cimg,C++,Cimg,我用c++编写了一个代码,使用CImg库在图像中添加噪声。现在我想加载带有噪声的图像,并使用中值滤波算法去除图像中的噪声。 下面是我的代码 int main() { int x; cout<<"Welcome to my app\n"; cout<<"Choose options below\n"; cout<<"1. Remove pepper 2. Add pepper\n"; cin>>x;
int main()
{
int x;
cout<<"Welcome to my app\n";
cout<<"Choose options below\n";
cout<<"1. Remove pepper 2. Add pepper\n";
cin>>x;
if (x==1)
{
cout<<"Needs help";
/*
* i tried to change the noise level to 0 but it did not work like below
* image.noise(0,2);
*
*/
}
else if(x==2)
{
//image file
CImg<unsigned char> image("new.bmp");
const unsigned char red[] = { 255,0,0 }, green[] = { 0,255,0 }, blue[] = { 0,0,255 };
image.noise(100,2);
image.save("new2.bmp");
CImgDisplay main_disp(image, "Image with Pepper noise");
while (!main_disp.is_closed())
{
main_disp.wait();
}
}
getchar();
return 0;
}
intmain()
{
int x;
cout根据函数的定义,你会得到如下结果:
#include <algorithm>
using namespace std;
// ...
int ksize = 3; // 5, 7, N and so on... for NxN kernel
int ksize2 = ksize/2;
vector<uchar> kernel(ksize*ksize, 0);
for (int i=ksize2;i<image.dimx() - ksize2;i++)
for (int j=ksize2;j<image.dimy() - ksize2;j++)
for (int k=0;k<3;k++) {
// prepare kernel
int n = 0;
for(int l = -ksize2; l <= ksize2; l++)
for(int m = -ksize2; m <= ksize2; m++)
kernel[n++] = image(i + l,j + m,0,k);
// using std::algorithm to find median
sort(kernel.begin(), kernel.end());
// simple assign median value to created empty image
medianFilteredImage(i, j, 0, k) = kernel[kernel.size()/2]; // median is here now
}
}
}
#包括
使用名称空间std;
// ...
int ksize=3;//5、7、N等等…对于NxN内核
int ksize2=ksize/2;
向量核(ksize*ksize,0);
对于(int i=ksize2;i根据函数的定义,您将得到如下结果:
#include <algorithm>
using namespace std;
// ...
int ksize = 3; // 5, 7, N and so on... for NxN kernel
int ksize2 = ksize/2;
vector<uchar> kernel(ksize*ksize, 0);
for (int i=ksize2;i<image.dimx() - ksize2;i++)
for (int j=ksize2;j<image.dimy() - ksize2;j++)
for (int k=0;k<3;k++) {
// prepare kernel
int n = 0;
for(int l = -ksize2; l <= ksize2; l++)
for(int m = -ksize2; m <= ksize2; m++)
kernel[n++] = image(i + l,j + m,0,k);
// using std::algorithm to find median
sort(kernel.begin(), kernel.end());
// simple assign median value to created empty image
medianFilteredImage(i, j, 0, k) = kernel[kernel.size()/2]; // median is here now
}
}
}
#包括
使用名称空间std;
// ...
int ksize=3;//5、7、N等等…对于NxN内核
int ksize2=ksize/2;
向量核(ksize*ksize,0);
对于(int i=ksize2;i