云中双边滤波器——基于opencv图像结构

概念理解:对于传统的维纳滤波和高斯滤波，都只是在像素点邻域范围内进行卷积操作，而双边滤波又加入了像素点差值的限制，这样对于边缘点像素变化很大的地方，便不会受到滤波影响了，也就达到了保存边缘的滤波效果。

代码：

void bilateralBlur(IplImage* input_img, IplImage* output_img, int sigmaS, int sigmaR)
{
// Create Gaussian/Bilateral filter --- mask --- 
int length = 9; 
std::vector<float> mask(length); 
for (int i = 0; i < length; i++) 
{ 
mask[i] = exp(-0.5*((i*i)/(sigmaS*sigmaS))); 
//fprintf( stderr, "i = %d, value= %f \n", i, mask[i]); 
}
int m_width = input_img->width ; 
int m_height= input_img->height ; //ImageData 
uchar* src_img= (uchar*) input_img->imageData ; //Ausgangs bild ist genau so groß wie das Eingangsbild! 
uchar* dst_img =(uchar*) output_img->imageData ; 
double wp = 0.0, k = 0.0;

//evtl. mit y=-length/2; y<=m_height-length/2; y+=4 
for(int y=0; y<m_height; y+=1) 
{ 
for (int x=0; x<m_width; x+=1)
{

int centerPix =x + y*m_width;

for (int j=-length/2;j <=length/2;j+=1)
{ 
for (int i=-length/2;i<=length/2;i+=1)
{

int curPix = x+i+(y+j)*(m_width);

//spatial diff 
double delta = sqrt(double(i*i+j*j)); 
double euklidDiff=exp(-0.5 * pow(delta/sigmaS,2)); 
double intens = src_img[centerPix]-src_img[curPix]; 
double factor = exp(-0.5 * pow(intens/sigmaR,2)) * euklidDiff;

wp += factor * src_img[curPix]; 
k += factor;

}
}
dst_img[centerPix] = wp/k; 
wp=0.0; 
k=0.0;
}
}
}