OpenCV有转换为极坐标和后面的代码，这种转换对于通过关联或者以其他方式创建对象的以对象为中心的“旋转无关”表示来说很有用。以显示每个极坐标以及它们的联合图像。下面的图像应该是self_explanatory。极坐标绘图以角度为横轴，半径为纵轴，以使4个峰值对应于输入图像的4个角。代码（带有OpenCV的C++）已附带。 
//================================
// Name : PolarCoord.cpp
// Author : V.Ivanchenko [email protected]
// Version :
// Copyright : Your copyright notice
// Description : Hello World in C++, Ansi-style
//======================================
#include <iostream>
#include "opencv.hpp"
using namespace std;
using namespace cv;
#define VALID(x, y, w, h) ((x)>=0 && (y)>=0 && (x)<(w) && (y)<(h)) // validates index
/*
* 1. Original binary image HxW CV_8U
* |
* |
* V
* 2. Two coordinate Mats HxW CV_32F
* |
* |
* V
* 3. Visualization CV_8U
* a. gray HxW for a single coordinate image
* b. binary Rx360 for two coordinate images
*/
// convert a binary 2D image into two Mats with float coordiantes
void imageToCoord(const Mat& img, Mat& X, Mat& Y, bool centered = true) {
if (img.empty())
return;
int h = img.rows;
int w = img.cols;
X.create(h, w, CV_32F);
Y.create(h, w, CV_32F);
float Cx = w/2.0f;
float Cy = h/2.0f;
for (int i=0; i<h; ++i){
const uchar* img_row = img.ptr<uchar>(i);
float* x_row = X.ptr<float>(i);
float* y_row = Y.ptr<float>(i);
for (int j=0; j<w; ++j) {
if (img_row[j]>0) {
float x = j;
float y = i;
if (centered) {
x-=Cx;
y-=Cy;
}
x_row[j] = x;
y_row[j] = y;
}
} // j
} // i
} //imageToCoord()
// convert a single float ploar coord Mat to a gray image
void polarToImg(const Mat& PolarCoord, Mat& img) {
if (PolarCoord.empty())
return;
int h = PolarCoord.rows;
int w = PolarCoord.cols;
img.create(h, w, CV_8U);
float maxVal = std::numeric_limits<float>::min();
// find maxVal
for (int i=0; i<h; ++i){
const float* x_row = PolarCoord.ptr<float>(i);
for (int j=0; j<w; ++j) {
if (maxVal < x_row[j])
maxVal = x_row[j];
} // j
} // i
// create an image
if (maxVal>0) {
float k = 255.0/maxVal;
for (int i=0; i<h; ++i){
uchar* img_row = img.ptr<uchar>(i);
const float* x_row = PolarCoord.ptr<float>(i);
for (int j=0; j<w; ++j) {
img_row[j] = saturate_cast<uchar>(k*x_row[j]);
}// j
} // i
} // if
} // plarToImg()
// convert two polar coord Mats to a binary image
void polarToImg(const Mat& radius, const Mat& angle, Mat& img) {
if (angle.empty() || radius.empty())
return;
int h = angle.rows;
int w = angle.cols;
assert(radius.cols==w && radius.rows==h);
const int imgH = sqrt(h*h+w*w)+0.5f; // radius
const int imgW = 360; // angle, deg
img.create(imgH, imgW, CV_8U);
// create an image
for (int i=0; i<h; ++i){
const float* ang_row = angle.ptr<float>(i);
const float* r_row = radius.ptr<float>(i);
for (int j=0; j<w; ++j) {
int x = ang_row[j] + 0.5f;
int y = r_row[j] + 0.5f;
if (x>0) {
cout<<x<<endl;
}
if (VALID(x, y, imgW, imgH))
img.at<uchar>(y, x) = 255;
else {
cout<<"Invalid x, y: "<<x<<", "<<y<<endl;
}
}// j
} // i
} // plarToImg()
int main() {
cout << "Cartesian to polar" << endl; // prints "Syntax training in openCV"
const int W=400, H=400;
Mat Minput(H, W, CV_8U);
Minput(Rect(W/4, H/4, W/2, H/2)) = 255;
Mat X, Y, Angle, Radius, Mr, Mang, Mpolar;
// processing
imageToCoord(Minput, X, Y); // extract coordinates
cartToPolar(X, Y, Radius, Angle, true);// convert coordiantes
// visualize
polarToImg(Radius, Mr);
polarToImg(Angle, Mang);
polarToImg(Radius, Angle, Mpolar);
// debug
//cout<<Mpolar<<endl;
namedWindow("input", 0);
namedWindow("angle", 0);
namedWindow("radius", 0);
namedWindow("Polar", 0);
const int winw=200, winh=200;
resizeWindow("input", winw, winh);
resizeWindow("angle", winw, winh);
resizeWindow("radius", winw, winh);
resizeWindow("Polar", 360, (int)sqrt(H*H + W*W));
moveWindow("input", 0, 0);
moveWindow("angle", winw, 0);
moveWindow("radius", 2*winw, 0);
moveWindow("Polar", 3*winw, 0);
imshow("input", Minput);
imshow("angle", Mang);
imshow("radius", Mr);
imshow("Polar", Mpolar);
waitKey(-1);
return 0;
}
我读从软件这些值（XYZ，az_elev_r），并不能更改。 – Shahgee