图像处理 之 同态滤波

借别人的代码，出处，忘记了，好像是一个毕业设计：

 这个滤波器设计的好像过了！ 

double D0=180;

void ILPF(CvMat* src, const double D0)
{
int i, j;
int state = -1;
double tempD;
long width, height;
width = src->width;
height = src->height;

long x, y;
x = width / 2;
y = height / 2;

CvMat* H_mat;
H_mat = cvCreateMat(src->height,src->width, CV_64FC2);
for(i = 0; i < height; i++)
{
for(j = 0; j < width; j++)
{
if(i > y && j > x)
{
state = 3;
}
else if(i > y)
{
state = 1;
}
else if(j > x)
{
state = 2;
}
else
{
state = 0;
}

switch(state)
{
case 0:
tempD = (double) (i * i + j * j);tempD = sqrt(tempD);break;
case 1:
tempD = (double) ((height - i) * (height - i) + j * j);tempD = sqrt(tempD);break;
case 2:
tempD = (double) (i * i + (width - j) * (width - j));tempD = sqrt(tempD);break;
case 3:
tempD = (double) ((height - i) * (height - i) + (width - j) * (width - j));tempD = sqrt(tempD);break;
default:
break;
}

//二维高斯高通滤波器

tempD = 1 - exp(-0.5 * pow(tempD / D0, 2));
((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2] = tempD;
((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2 + 1] = 0.0;

//////二维理想高通滤波器

//if(tempD <= D0)
//{
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2] = 0.0;
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2 + 1] = 0.0;
//}
//else
//{
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2] = 1.0;
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2 + 1] = 0.0;
//}

// //2阶巴特沃思高通滤波器
// tempD = 1 / (1 + pow(D0 / tempD, 2 * 2));
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2] = tempD;
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2 + 1] = 0.0;

// //增长率为2二维指数高通滤波器
// tempD = exp(-pow(D0 / tempD, 2));
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2] = tempD;
// ((double*)(H_mat->data.ptr + H_mat->step * i))[j * 2 + 1] = 0.0;

}
}

cvMulSpectrums(src, H_mat, src, CV_DXT_ROWS);
cvReleaseMat(&H_mat);

}

void CMipImagePro::TongTai_Filter(IplImage* pCelGrayImg)
{

unsigned int i;
CString str;

IplImage* im = pCelGrayImg;

IplImage * realInput;
IplImage * imaginaryInput;
IplImage * complexInput;
int dft_M, dft_N;
CvMat* dft_A, tmp, *dft_B;
IplImage * image_Re;
IplImage * image_Im;
double m, M;

realInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
imaginaryInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
complexInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 2);

cvScale(im, realInput, 1.0, 0.0);
cvZero(imaginaryInput);
cvMerge(realInput, imaginaryInput, NULL, NULL, complexInput);

dft_M = cvGetOptimalDFTSize( im->height - 1 );
dft_N = cvGetOptimalDFTSize( im->width - 1 );
dft_B = cvCreateMat( dft_M, dft_N, CV_64FC2 );
dft_A = cvCreateMat( dft_M, dft_N, CV_64FC2 );
cvZero(dft_A);
cvZero(dft_B);

image_Re = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
image_Im = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);

cvGetSubRect( dft_A,&tmp, cvRect(0,0, im->width, im->height));
cvCopy( complexInput, &tmp, NULL );

cvDFT( dft_A, dft_A, CV_DXT_FORWARD, complexInput->height );

ILPF(dft_A, D0);

cvDFT( dft_A, dft_A, CV_DXT_INVERSE , complexInput->height );

cvNamedWindow("win", 0);
cvNamedWindow("magnitude", 0);
cvShowImage("win", im);

cvSplit( dft_A, image_Re, image_Im, 0, 0 );

cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
cvScale(image_Re, image_Re, 1.0/(M-m), 1.0*(-m)/(M-m));

//cvGetSubRect( dft_A,&tmp, cvRect(0,0, im->width, im->height));
//cvCopy( image_Re, &pCelGrayImg, NULL );

cvShowImage("magnitude", image_Re);

}