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卷积操作的C++实现
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
using namespace std;
using namespace cv;
Mat Kernel_test_3_3 = (
Mat_<double>(3, 3) <<
0, -1, 0,
-1, 5, -1,
0, -1, 0);
void Convlution(Mat InputImage, Mat OutputImage, Mat kernel)
{
//计算卷积核的半径
int sub_x = kernel.cols / 2;
int sub_y = kernel.rows / 2;
//遍历图片
for (int image_y = 0; image_y < InputImage.rows - 2 * sub_y; image_y++)
{
for (int image_x = 0; image_x < InputImage.cols - 2 * sub_x; image_x++)
{
int pix_value = 0;
for (int kernel_y = 0; kernel_y < kernel.rows; kernel_y++)
{
for (int kernel_x = 0; kernel_x < kernel.cols; kernel_x++)
{
double weihgt = kernel.at<double>(kernel_y, kernel_x);
int value = (int)InputImage.at<uchar>(image_y + kernel_y, image_x + kernel_x);
pix_value += weihgt*value;
}
}
OutputImage.at<uchar>(image_y + sub_y, image_x + sub_x) = (uchar)pix_value;
}
}
}
int main()
{
Mat srcImage = imread("1.jpg", 0);
namedWindow("srcImage", WINDOW_AUTOSIZE);
imshow("原图", srcImage);
//filter2D卷积
Mat dstImage_oprncv(srcImage.rows, srcImage.cols, CV_8UC1, Scalar(0));;
filter2D(srcImage, dstImage_oprncv, srcImage.depth(), Kernel_test_3_3);
imshow("filter2D卷积图", dstImage_oprncv);
imwrite("1.jpg", dstImage_oprncv);
//自定义卷积
Mat dstImage_mycov(srcImage.rows, srcImage.cols, CV_8UC1, Scalar(0));
Convlution(srcImage, dstImage_mycov, Kernel_test_3_3);
imshow("卷积图3", dstImage_mycov);
imwrite("2.jpg", dstImage_mycov);
waitKey(0);
return 0;
}
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