opencv复杂一点的变换

cvPyrUP将现有的图像在每个维度上放大两倍

cvPyrUP(

IplImage *src,

IplImage *dst,

IplFilter filter=CV_GAUSSIAN_5x5

);

Canny边缘检测
void Canny(InputArray src,OutputArray dst,double threshold1, double threshold2, int apertureSize=3,bool L2gradient=false )

参数详解：

src：源图像 
dst：目标图像。 
threshold1：第一个滞后性阈值。 
threshold2：第二个滞后性阈值。 
apertureSize：表示应用Sobel算子的孔径大小，其有默认值3。 
L2gradient：一个计算图像梯度幅值的标识，有默认值false。

需要注意的是，这个函数threshold1和threshold2两者的小者用于边缘连接，而大者用来控制强边缘的初始段， 推荐的高低阈值比在2:1到3:1之间。

下面是将一幅图调用两次doPyrdown，再用canny处理的例子。

#include "highgui.h"
#include "cv.h"
IplImage* out;
IplImage* doPyrdown(IplImage* in)
{
assert(in->width % 2 == 0 && in->height % 2 == 0);
out = cvCreateImage(
cvSize(in->width / 2, in->height / 2),
in->depth,
in->nChannels
);
cvPyrDown(in, out, CV_GAUSSIAN_5x5);
return (out);
};
IplImage* doCanny(IplImage *in,
double lowThresh,
double highTresh,
int aperture
) {

if (in->nChannels != 1) return (0);
IplImage *out = cvCreateImage(
cvSize(in->width, in->height),
IPL_DEPTH_8U,
1
);
cvCanny(in, out, lowThresh, highTresh, aperture);
return(out);
};
int main(int argc, char** argv)
{
IplImage* img = cvLoadImage("1.jpg", 0);
cvNamedWindow("原图", CV_WINDOW_AUTOSIZE);
cvShowImage("原图", img);
  out = doPyrdown(img);
  out = doPyrdown(out);
out = doCanny(img, 2, 3, 3);

cvNamedWindow("两次缩放和边缘检测", CV_WINDOW_AUTOSIZE);

cvShowImage("两次缩放和边缘检测", out);
cvWaitKey(0);
cvReleaseImage(&out);
cvDestroyWindow("两次缩放和边缘检测");
cvReleaseImage(&img);
cvDestroyWindow("原图");
return 0;
}