OpenCV 之 数字图像

1  数字图像

数字图像可看作一个 数值矩阵, 其中的每个 元素代表一个 像素点，如下图所示：

2  存储方式

M 行 N 列图像的存储位数: b = M * N * k   ( L=2^k, l ∈ [0, L-1], l 为灰度值 )

2.1  灰度图

OpenCV 中，灰度图的存储形式如下：

2.2  RGB图像

OpenCV中，RGB图像以 BGR 的顺序存储，如下：

2.3  Mat 类

Mat = 矩阵头 + 指针（指向包含像素值的矩阵），其有如下特点：

1)  矩阵头包含矩阵大小，存储函数，存储地址等信息

2)  使用 OpenCV 的接口函数，无需考虑内存管理

3)  执行赋值算子 “=” 或 拷贝构造函数时，仅仅复制矩阵头 (matrix header)

4)  图像矩阵的复制，应该使用 clone() 和 copyTo() 函数

#include <iostream>
#include "opencv2/core/core.hpp"

using namespace std;
using namespace cv;

int main(int,char**)
{
    // 1) 构造函数
    Mat M(,, CV_8UC3, Scalar(,,));
    cout << "M = " << endl << " " << M << endl << endl;

    // 2) create 函数
    M.create(,, CV_8UC());
    cout << "M = "<< endl << " "  << M << endl << endl;

    // 3) 多维矩阵
    int sz[] = {,,};
    Mat L(,sz, CV_8UC(), Scalar::all());

    // 4) MATLAB 风格 eye, ones or zero
    Mat E = Mat::eye(, , CV_64F);
    cout << "E = " << endl << " " << E << endl << endl;
    Mat O = Mat::ones(, , CV_32F);
    cout << "O = " << endl << " " << O << endl << endl;
    Mat Z = Mat::zeros(, , CV_8UC1);
    cout << "Z = " << endl << " " << Z << endl << endl;

    // 5) 3x3 双精度
    Mat C = (Mat_<double>(,) << , -, , -, , -, , -, );
    cout << "C = " << endl << " " << C << endl << endl;

    //! [clone]
    Mat RowClone = C.row().clone();
    cout << "RowClone = " << endl << " " << RowClone << endl << endl;

    // 6) 随机值填充矩阵
    Mat R = Mat(, , CV_8UC3);
    randu(R, Scalar::all(), Scalar::all());

    // 演示输出格式
    cout << "R (default) = " << endl <<        R           << endl << endl;
    cout << "R (python)  = " << endl << format(R, Formatter::FMT_PYTHON) << endl << endl;
    cout << "R (numpy)   = " << endl << format(R, Formatter::FMT_NUMPY ) << endl << endl;
    cout << "R (csv)     = " << endl << format(R, Formatter::FMT_CSV   ) << endl << endl;
    cout << "R (c)       = " << endl << format(R, Formatter::FMT_C     ) << endl << endl;

    vector<float> v;
    v.push_back((float)CV_PI);
    v.push_back();
    v.push_back(3.01f);
    cout << "Vector of floats via Mat = " << Mat(v) << endl << endl;
}

3  邻域

D 定义为像素点 p(x, y) 和 q(s, t)的距离

3.1  四邻域 -  十字格

D₄ = |x - s| + |y - t| = 1

$\quad \begin{bmatrix} 2 & 1 & 2 \\ 1 & 0 & 1 \\ 2 & 1 & 2 \end{bmatrix} $

3.2  八邻域 - 田字格

D₈ = max(|x - s|, |y - t|) = 1

$\quad \begin{bmatrix} 1 & 1 & 1 \\ 1 & 0 & 1 \\ 1 & 1 & 1 \end{bmatrix} $

4  代码示例 

4.1  读图和显示 

OpenCV 中，图像读取和显示的函数名，和 Matlab 中的一致, 即 imread 和 imshow

#include "opencv2/highgui/highgui.hpp"
using namespace cv;

int main(int argc, char ** argv)    // int main()
{
    Mat img = imread(argv[] - );  // Mat img = imread("E:/.../feng.jpg");
    if(img.empty()) 
　　　　return -;
    namedWindow("Example", CV_WINDOW_AUTOSIZE);
    imshow("Example", img);
    waitKey();
}

4.2  遍历像素

4.2.1  efficient method

Mat& ScanImageAndReduceC(Mat& I, const uchar* const table)
{
    // accept only char type matrices
    CV_Assert(I.depth() == CV_8U);
    int channels = I.channels();
    int nRows = I.rows;
    int nCols = I.cols * channels;
    if (I.isContinuous())
    {
        nCols *= nRows;
        nRows = ;
    }
    int i,j;
    uchar* p;
    for( i = ; i < nRows; ++i)
    {
        p = I.ptr<uchar>(i);
        for ( j = ; j < nCols; ++j)
        {
            p[j] = table[p[j]];
        }
    }
    return I;
}

 4.2.2  iterator method

Mat& ScanImageAndReduceIterator(Mat& I, const uchar* const table)
{
    // accept only char type matrices
    CV_Assert(I.depth() == CV_8U);
    const int channels = I.channels();
    switch(channels)
    {
    case :
        {
            MatIterator_<uchar> it, end;
            for( it = I.begin<uchar>(), end = I.end<uchar>(); it != end; ++it)
                *it = table[*it];
            break;
        }
    case :
        {
            MatIterator_<Vec3b> it, end;
            for( it = I.begin<Vec3b>(), end = I.end<Vec3b>(); it != end; ++it)
            {
                (*it)[] = table[(*it)[]];
                (*it)[] = table[(*it)[]];
                (*it)[] = table[(*it)[]];
            }
        }
    }
    return I;
}