目錄
- 原理
- 源碼
-
- RotateImage
- 主函數
- 效果
- 完整源碼
- 速度優化
-
- 源碼
- 優化效果
平台:Windows 10 20H2
Visual Studio 2015
OpenCV 4.5.3
本文算法改進自圖形算法與實戰:6.圖像運動專題(5)圖像旋轉-基于近鄰插值的圖像旋轉 —— 進擊的CV
原理
将旋轉後圖像的像素點映射回原圖像,找到它的采樣點,即旋轉的逆變換。映射的結果不會都是整數像素點,那麼旋轉後的點的像素值由與采樣點最鄰近的像素值表示,這就是最近鄰插值。
![](https://img.laitimes.com/img/9ZDMuAjOiMmIsIjOiQnIsIiclRnblN2XjlGcjYTMfhHLlN3XnxCM38FdsYkRGZkRG9lcvx2bjxyNx8VZ6l2cs40TaZjbDJXN0cVW2oVbMVTQClGVF5UMR9Fd4VGdsATNfd3bkFGazxycykFaKdkYzZUbapXNXlleSdVY2pESa9VZwlHdssmch1mclRXY39CXldWYtlWPzNXZj9mcw1ycz9WL49zZwpmL0AzMxIzY1cTOmVGMkljM5cDMhRDO1EzYmRDNklTZ4EzLc52YucWbp5GZzNmLn9Gbi1yZtl2Lc9CX6MHc0RHaiojIsJye.jpg)
改變尺寸的圖像旋轉
這種旋轉是将旋轉後的圖像内容完全顯示出來,是以要确定新的圖像的尺寸。
源碼
RotateImage
Mat RotateImage(Mat src, double angle)
{
int x0, y0, x1, y1;
angle = angle * 3.1415926535897932384626433832795 / 180;
int dx = abs((int)src.cols*cos(angle)) + abs((int)src.rows*sin(angle));
int dy = abs((int)src.cols*sin(angle)) + abs((int)src.rows*cos(angle));
Mat dst(dy, dx, CV_8UC3, Scalar(0)); //建立新圖像
for (x1 = 0; x1 < dst.cols; x1++)
{
for (y1 = 0; y1 < dst.rows; y1++)
{
double fx0, fy0;
double fx1, fy1;
double R;
double sita, sita0, sita1;
//将圖檔中點設為坐标原點
fx1 = x1 - dst.cols / 2;
fy1 = y1 - dst.rows / 2;
R = sqrt(fx1 * fx1 + fy1 * fy1); //極徑
sita = angle;
sita1 = atan2(fy1, fx1); //新點極角
sita0 = sita1 + sita; //舊點極角
//舊點直角坐标(中點為坐标原點)
fx0 = R * cos(sita0);
fy0 = R * sin(sita0);
//舊點直角坐标(坐标原點在角上)
x0 = fx0 + src.cols / 2 + 0.5;
y0 = fy0 + src.rows / 2 + 0.5;
if (x0 >= 0 && x0 < src.cols && y0 >= 0 && y0 < src.rows)
{
dst.at<Vec3b>(Point(x1, y1)) = src.at<Vec3b>(Point(x0, y0));
}
else
dst.at<Vec3b>(Point(x1, y1)) = 0;
}
}
return dst;
}
主函數
int main(int argc, char * argv[])
{
Mat src;
src = imread("D:\\Work\\OpenCV\\Workplace\\Test_1\\4.jpg");
imshow("原圖", src);
for (short i = -360; i <= 360; ++i)
{
imshow("輸出", RotateImage(src, i));
waitKey(1);
}
waitKey(0);
return 0;
}
效果
完整源碼
#include <opencv2\opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
Mat RotateImage(Mat src, double angle)
{
int x0, y0, x1, y1;
angle = angle * 3.1415926535897932384626433832795 / 180;
int dx = abs((int)src.cols*cos(angle)) + abs((int)src.rows*sin(angle));
int dy = abs((int)src.cols*sin(angle)) + abs((int)src.rows*cos(angle));
Mat dst(dy, dx, CV_8UC3, Scalar(0)); //建立新圖像
for (x1 = 0; x1 < dst.cols; x1++)
{
for (y1 = 0; y1 < dst.rows; y1++)
{
double fx0, fy0;
double fx1, fy1;
double R;
double sita, sita0, sita1;
//将圖檔中點設為坐标原點
fx1 = x1 - dst.cols / 2;
fy1 = y1 - dst.rows / 2;
R = sqrt(fx1 * fx1 + fy1 * fy1); //極徑
sita = angle;
sita1 = atan2(fy1, fx1); //新點極角
sita0 = sita1 + sita; //舊點極角
//舊點直角坐标(中點為坐标原點)
fx0 = R * cos(sita0);
fy0 = R * sin(sita0);
//舊點直角坐标(坐标原點在角上)
x0 = fx0 + src.cols / 2 + 0.5;
y0 = fy0 + src.rows / 2 + 0.5;
if (x0 >= 0 && x0 < src.cols && y0 >= 0 && y0 < src.rows)
{
dst.at<Vec3b>(Point(x1, y1)) = src.at<Vec3b>(Point(x0, y0));
}
else
dst.at<Vec3b>(Point(x1, y1)) = 0;
}
}
return dst;
}
int main(int argc, char * argv[])
{
Mat src;
src = imread("D:\\Work\\OpenCV\\Workplace\\Test_1\\4.jpg");
imshow("原圖", src);
for (short i = -360; i <= 360; ++i)
{
imshow("輸出", RotateImage(src, i));
waitKey(1);
}
waitKey(0);
return 0;
}
速度優化
源碼
Mat RotateImage(Mat src, float angle)
{
int x0, y0, x1, y1;
angle = angle * 3.1415926535897932384626433832795 / 180;
float sin_sita = sin(angle), cos_sita = cos(angle);
Mat dst(abs((int)src.cols*sin_sita) + abs((int)src.rows*cos_sita), abs((int)src.cols*cos_sita) + abs((int)src.rows*sin_sita), CV_8UC3, Scalar(0)); //建立新圖像
for (x1 = 0; x1 < dst.cols; ++x1)
{
for (y1 = 0; y1 < dst.rows; ++y1)
{
float fx1, fy1;
//将圖檔中點設為坐标原點
fx1 = x1 - dst.cols / 2;
fy1 = y1 - dst.rows / 2;
//舊點直角坐标(坐标原點在角上)
x0 = fx1*cos_sita - fy1*sin_sita + src.cols / 2 + 0.5;
y0 = fx1*sin_sita + fy1*cos_sita + src.rows / 2 + 0.5;
if (x0 >= 0 && x0 < src.cols && y0 >= 0 && y0 < src.rows)
{
dst.at<Vec3b>(Point(x1, y1)) = src.at<Vec3b>(Point(x0, y0));
}
else
dst.at<Vec3b>(Point(x1, y1)) = 0;
}
}
return dst;
}
優化效果
旋轉一幅1200×562的圖像
用時幾乎是原來的1/2