如何以优雅的方式使用OpenCV,c ++检索偶/奇索引中的值? [英] How to retrieve values in even/odd indices using OpenCV, c++ in an elegant way?
问题描述
考虑一下,我有以下矩阵
Consider, I have the following matrix
0 1 2 3
4 5 6 7
8 9 10 11
12 13 14 15
我想在不使用for循环的情况下检索偶数索引(x和y索引均为偶数)中的值.
I want to retrieve the values in even indices (both x and y indices are even) without using for loop.
0 2
8 10
我有大尺寸的图像(许多5000 * 5000 +灰度矩阵).使用for循环似乎并不是最好的方法.我想听听是否有比for循环更好的方法.
I have big sized images (many of 5000*5000+ grayscale matrices). Using for loop doesn't seem to be the best way. I'd like to hear if there is better way than for loops.
我尝试使用以下掩码,然后执行操作,但效率不高,因为我需要进行4 * n ^ 2乘法而不是n ^ 2(假设原始图像为2n * 2n)
I tried using the following mask, then do the operations but it is not efficient because I need to do 4*n^2 multiplication rather than n^2(Assume original image is 2n*2n)
1 0 1 0
0 0 0 0
1 0 1 0
0 0 0 0
请注意,我在矩阵上执行了多项操作.感谢您的帮助.
Note that, I do multiple operations on the matrix. Any help is appreciated.
预先感谢
推荐答案
您可以删除无用的行和列,并以原始矩阵大小的一半处理矩阵.
You can remove the useless rows and columns, and work on a matrix with half the size of the original matrix.
您可以使用resize
函数并使用最接近的插值轻松完成此操作:
You can do this easily with the resize
function, with nearest interpolation:
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main(int argc, char **argv)
{
Mat1b mat = (Mat1b(4,4) << 0, 1, 2, 3,
4, 5, 6, 7,
8, 9, 10, 11,
12, 13, 14, 15);
Mat1b res;
resize(mat, res, Size(0, 0), 0.5, 0.5, INTER_NEAREST);
cout << "Mat:" << endl << mat << endl << endl;
cout << "Res:" << endl << res << endl;
return 0;
}
然后res
中的值仅是您需要的索引处的值:
Then the values in res
are only the values at the indices you need:
Mat:
[0, 1, 2, 3;
4, 5, 6, 7;
8, 9, 10, 11;
12, 13, 14, 15]
Res:
[0, 2;
8, 10]
为了将值恢复到原始位置,您可以使用Kronecker产品(在OpenCV中不可用,但可以轻松实现).这将产生:
In order to restore the values to original position, you can use the Kronecker product (not available in OpenCV, but can be easily implemented) with a suitable pattern. This will produce:
Mat:
[0, 1, 2, 3;
4, 5, 6, 7;
8, 9, 10, 11;
12, 13, 14, 15]
Res:
[0, 2;
8, 10]
Res Modified:
[1, 3;
9, 11]
Restored:
[1, 0, 3, 0;
0, 0, 0, 0;
9, 0, 11, 0;
0, 0, 0, 0]
代码:
#include <opencv2/opencv.hpp>
#include <algorithm>
#include <iostream>
using namespace cv;
using namespace std;
Mat kron(const Mat A, const Mat B)
{
CV_Assert(A.channels() == 1 && B.channels() == 1);
Mat1d Ad, Bd;
A.convertTo(Ad, CV_64F);
B.convertTo(Bd, CV_64F);
Mat1d Kd(Ad.rows * Bd.rows, Ad.cols * Bd.cols, 0.0);
for (int ra = 0; ra < Ad.rows; ++ra)
{
for (int ca = 0; ca < Ad.cols; ++ca)
{
Kd(Range(ra*Bd.rows, (ra + 1)*Bd.rows), Range(ca*Bd.cols, (ca + 1)*Bd.cols)) = Bd.mul(Ad(ra, ca));
}
}
Mat K;
Kd.convertTo(K, A.type());
return K;
}
int main(int argc, char **argv)
{
Mat1b mat = (Mat1b(4, 4) << 0, 1, 2, 3,
4, 5, 6, 7,
8, 9, 10, 11,
12, 13, 14, 15);
Mat1b res;
resize(mat, res, Size(0, 0), 0.5, 0.5, INTER_NEAREST);
cout << "Mat:" << endl << mat << endl << endl;
cout << "Res:" << endl << res << endl << endl;
// Work on Res
res += 1;
cout << "Res Modified:" << endl << res << endl << endl;
// Define the pattern
Mat1b pattern = (Mat1b(2,2) << 1, 0,
0, 0);
// Apply Kronecker product
Mat1b restored = kron(res, pattern);
cout << "Restored:" << endl << restored << endl << endl;
return 0;
}
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