LINUX 下Open cv练习使用小记（2）
第二节记录一下自己学习图像遍历的一点点代码，摘自《opencv2编程手册》（张静译）
第一个代码是最简单的强行修改像素（添加椒盐噪声）
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp> void salt(cv::Mat &image, int n) { int i,j;
for (int k=; k<n; k++) { // rand() is the MFC random number generator
i= rand()%image.cols;
j= rand()%image.rows; if (image.channels() == ) { // gray-level image image.at<uchar>(j,i)= ; } else if (image.channels() == ) { // color image image.at<cv::Vec3b>(j,i)[]= ;
image.at<cv::Vec3b>(j,i)[]= ;
image.at<cv::Vec3b>(j,i)[]= ;
}
}
} int main()
{
srand(cv::getTickCount()); // init random number generator cv::Mat image= cv::imread("../cat.jpg",); salt(image,); cv::namedWindow("Image");
cv::imshow("Image",image); cv::imwrite("salted.bmp",image); cv::waitKey(); return ;
}
书上的注释为image.<unchar>(j,i)=255，将i行j列的数据变为白色。
第二个程序才开始真正的遍历
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp> void colorReduce0(cv::Mat &image, int div=) { int nl= image.rows; // 每行的像素数目
int nc= image.cols * image.channels(); // total number of elements per line for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j);//此句返回j行的首地址 for (int i=; i<nc; i++) { // process each pixel --------------------- data[i]= data[i]/div*div + div/; // end of pixel processing ---------------- } // end of line
}
} int main()
{
//srand(cv::getTickCount()); // init random number generator cv::Mat image= cv::imread("../cat.jpg"); colorReduce0(image); cv::namedWindow("Image");
cv::imshow("Image",image); cv::imwrite("cat.jpg",image); cv::waitKey(); return ;
}
这个程序写的是对小猫的颜色进行缩减,效果如下
另，对像素的操作可以采用
*data++ =*data/div*div + div/
来书写
接下来，我就继续看第二种颜色缩进的算法
void colorReduce1(cv::Mat &image, int div=) {
int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line
for (int j=; j<nl; j++) {
uchar* data= image.ptr<uchar>(j);
for (int i=; i<nc; i++) {
// process each pixel ---------------------
*data++= *data/div*div + div/;
// end of pixel processing ----------------
} // end of line
}
}
效果如下
到这里我就整个人变傻了。两个算法不是一样的吗- -，为什么效果差别这么大- -
算了，还是将人家给的代码放出吧，希望有大神指正
#include <iostream> #include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp> // using .ptr and []
void colorReduce0(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- data[i]= data[i]/div*div + div/; // end of pixel processing ---------------- } // end of line
}
} // using .ptr and * ++
void colorReduce1(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- *data++= *data/div*div + div/; // end of pixel processing ---------------- } // end of line
}
} // using .ptr and * ++ and modulo
void colorReduce2(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- int v= *data;
*data++= v - v%div + div/; // end of pixel processing ---------------- } // end of line
}
} // using .ptr and * ++ and bitwise
void colorReduce3(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line
int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- *data++= *data&mask + div/; // end of pixel processing ---------------- } // end of line
}
} // direct pointer arithmetic
void colorReduce4(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line
int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
int step= image.step; // effective width
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 // get the pointer to the image buffer
uchar *data= image.data; for (int j=; j<nl; j++) { for (int i=; i<nc; i++) { // process each pixel --------------------- *(data+i)= *data&mask + div/; // end of pixel processing ---------------- } // end of line data+= step; // next line
}
} // using .ptr and * ++ and bitwise with image.cols * image.channels()
void colorReduce5(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<image.cols * image.channels(); i++) { // process each pixel --------------------- *data++= *data&mask + div/; // end of pixel processing ---------------- } // end of line
}
} // using .ptr and * ++ and bitwise (continuous)
void colorReduce6(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols * image.channels(); // total number of elements per line if (image.isContinuous()) {
// then no padded pixels
nc= nc*nl;
nl= ; // it is now a 1D array
} int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- *data++= *data&mask + div/; // end of pixel processing ---------------- } // end of line
}
} // using .ptr and * ++ and bitwise (continuous+channels)
void colorReduce7(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols ; // number of columns if (image.isContinuous()) {
// then no padded pixels
nc= nc*nl;
nl= ; // it is now a 1D array
} int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 for (int j=; j<nl; j++) { uchar* data= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- *data++= *data&mask + div/;
*data++= *data&mask + div/;
*data++= *data&mask + div/; // end of pixel processing ---------------- } // end of line
}
} // using Mat_ iterator
void colorReduce8(cv::Mat &image, int div=) { // get iterators
cv::Mat_<cv::Vec3b>::iterator it= image.begin<cv::Vec3b>();
cv::Mat_<cv::Vec3b>::iterator itend= image.end<cv::Vec3b>(); for ( ; it!= itend; ++it) { // process each pixel --------------------- (*it)[]= (*it)[]/div*div + div/;
(*it)[]= (*it)[]/div*div + div/;
(*it)[]= (*it)[]/div*div + div/; // end of pixel processing ----------------
}
} // using Mat_ iterator and bitwise
void colorReduce9(cv::Mat &image, int div=) { // div must be a power of 2
int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 // get iterators
cv::Mat_<cv::Vec3b>::iterator it= image.begin<cv::Vec3b>();
cv::Mat_<cv::Vec3b>::iterator itend= image.end<cv::Vec3b>(); // scan all pixels
for ( ; it!= itend; ++it) { // process each pixel --------------------- (*it)[]= (*it)[]&mask + div/;
(*it)[]= (*it)[]&mask + div/;
(*it)[]= (*it)[]&mask + div/; // end of pixel processing ----------------
}
} // using MatIterator_
void colorReduce10(cv::Mat &image, int div=) { // get iterators
cv::Mat_<cv::Vec3b> cimage= image;
cv::Mat_<cv::Vec3b>::iterator it=cimage.begin();
cv::Mat_<cv::Vec3b>::iterator itend=cimage.end(); for ( ; it!= itend; it++) { // process each pixel --------------------- (*it)[]= (*it)[]/div*div + div/;
(*it)[]= (*it)[]/div*div + div/;
(*it)[]= (*it)[]/div*div + div/; // end of pixel processing ----------------
}
} void colorReduce11(cv::Mat &image, int div=) { int nl= image.rows; // number of lines
int nc= image.cols; // number of columns for (int j=; j<nl; j++) {
for (int i=; i<nc; i++) { // process each pixel --------------------- image.at<cv::Vec3b>(j,i)[]= image.at<cv::Vec3b>(j,i)[]/div*div + div/;
image.at<cv::Vec3b>(j,i)[]= image.at<cv::Vec3b>(j,i)[]/div*div + div/;
image.at<cv::Vec3b>(j,i)[]= image.at<cv::Vec3b>(j,i)[]/div*div + div/; // end of pixel processing ---------------- } // end of line
}
} // with input/ouput images
void colorReduce12(const cv::Mat &image, // input image
cv::Mat &result, // output image
int div=) { int nl= image.rows; // number of lines
int nc= image.cols ; // number of columns // allocate output image if necessary
result.create(image.rows,image.cols,image.type()); // created images have no padded pixels
nc= nc*nl;
nl= ; // it is now a 1D array int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 for (int j=; j<nl; j++) { uchar* data= result.ptr<uchar>(j);
const uchar* idata= image.ptr<uchar>(j); for (int i=; i<nc; i++) { // process each pixel --------------------- *data++= (*idata++)&mask + div/;
*data++= (*idata++)&mask + div/;
*data++= (*idata++)&mask + div/; // end of pixel processing ---------------- } // end of line
}
} // using overloaded operators
void colorReduce13(cv::Mat &image, int div=) { int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));
// mask used to round the pixel value
uchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0 // perform color reduction
image=(image&cv::Scalar(mask,mask,mask))+cv::Scalar(div/,div/,div/);
} #define NTESTS 14
#define NITERATIONS 20 int main()
{
int64 t[NTESTS],tinit;
cv::Mat image1;
cv::Mat image2; // timer values set to 0
for (int i=; i<NTESTS; i++)
t[i]= ; // repeat the tests several times
int n=NITERATIONS;
for (int k=; k<n; k++) { std::cout << k << " of " << n << std::endl; image1= cv::imread("../cat.jpg");
if (!image1.data)
return ; // using .ptr and []
tinit= cv::getTickCount();
colorReduce0(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++
tinit= cv::getTickCount();
colorReduce1(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++ and modulo
tinit= cv::getTickCount();
colorReduce2(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++ and bitwise
tinit= cv::getTickCount();
colorReduce3(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using direct pointer arithmetic
tinit= cv::getTickCount();
colorReduce4(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++ and bitwise with image.cols * image.channels()
tinit= cv::getTickCount();
colorReduce5(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++ and bitwise (continuous)
tinit= cv::getTickCount();
colorReduce6(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using .ptr and * ++ and bitwise (continuous+channels)
tinit= cv::getTickCount();
colorReduce7(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using Mat_ iterator
tinit= cv::getTickCount();
colorReduce8(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using Mat_ iterator and bitwise
tinit= cv::getTickCount();
colorReduce9(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using Mat_ iterator
tinit= cv::getTickCount();
colorReduce10(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using at
tinit= cv::getTickCount();
colorReduce11(image1);
t[]+= cv::getTickCount()-tinit; image1= cv::imread("../cat.jpg");
// using input/output images
tinit= cv::getTickCount();
cv::Mat result;
colorReduce12(image1, result);
t[]+= cv::getTickCount()-tinit; image2= result; image1= cv::imread("../cat.jpg");
// using input/output images
tinit= cv::getTickCount();
colorReduce13(image1);
t[]+= cv::getTickCount()-tinit; //------------------------------
} cv::namedWindow("Result");
cv::imshow("Result",image2);
cv::namedWindow("Image Result");
cv::imshow("Image Result",image1); // print average execution time
std::cout << std::endl << "-------------------------------------------" << std::endl << std::endl;
std::cout << "using .ptr and [] =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ and modulo =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ and bitwise =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using direct pointer arithmetic =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ and bitwise with image.cols * image.channels() =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ and bitwise (continuous) =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using .ptr and * ++ and bitwise (continuous+channels) =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using Mat_ iterator =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using Mat_ iterator and bitwise =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using MatIterator_ =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using at =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using input/output images =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl;
std::cout << "using overloaded operators =" << .*t[]/cv::getTickFrequency()/n << "ms" << std::endl; cv::waitKey();
return ;
}
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