opencv3/C++图像像素操作

RGB图像转灰度图

RGB图像转换为灰度图时通常使用：
 Gray=R×0.299+G×0.587+B×0.114
进行转换，以下尝试通过其他对图像像素操作的方式将RGB图像转换为灰度图像。

#include<opencv2/opencv.hpp>#include<math.h>using namespace cv;int main(){    //像素操作    Mat src,dst;    src = imread("E:/image/image/daibola.jpg");    if(src.empty())    {        printf("can not load image \n");        return -1;    }    namedWindow("input");    imshow("input",src);    dst.create(src.size(), src.type());    for(int row = 0; row < src.rows; row++)    {        for(int col = 0; col < src.cols; col++)        {            int b = src.at<Vec3b>(row, col)[0];            int g = src.at<Vec3b>(row, col)[1];            int r = src.at<Vec3b>(row, col)[2];            dst.at<Vec3b>(row, col)[0] = max(r,max(g,b));            dst.at<Vec3b>(row, col)[1] = max(r,max(g,b));            dst.at<Vec3b>(row, col)[2] = max(r,max(g,b));        }    }    namedWindow("output");    imshow("output",dst);    waitKey();}

同理使用min(r,min(g,b))可以看到由于选择了较小的灰度值图像会明显变暗：

图像线性增强

通过对图像像素操作（线性变换），实现图像的线性增强。

#include<opencv2/opencv.hpp>#include<math.h>using namespace cv;int main(){    Mat src1, dst;    src1 = imread("E:/image/image/im1.jpg");    if(src1.empty())    {        printf("can not load im1 \n");        return -1;    }    double alpha = 1.2, beta = 50;    dst = Mat::zeros(src1.size(), src1.type());    for(int row = 0; row < src1.rows; row++)    {        for(int col = 0; col < src1.cols; col++)        {            if(src1.channels() == 3)            {                int b = src1.at<Vec3b>(row, col)[0];                 int g = src1.at<Vec3b>(row, col)[1];                 int r = src1.at<Vec3b>(row, col)[2];                 dst.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(b*alpha + beta);                 dst.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(g*alpha + beta);                 dst.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(r*alpha + beta);             }            else if (src1.channels() == 1)            {                float v = src1.at<uchar>(row, col);                 dst.at<uchar>(row, col) = saturate_cast<uchar>(v*alpha + beta);            }        }    }    namedWindow("output",CV_WINDOW_AUTOSIZE);    imshow("output", dst);    waitKey();    return 0;}

掩膜操作调整图像对比度

使用一个3×3掩模增强图像对比度：

#include<opencv2/opencv.hpp>#include<math.h>using namespace cv;int main(){    Mat src, dst;    src = imread("E:/image/image/daibola.jpg");    CV_Assert(src.depth() == CV_8U);    if(!src.data)    {        printf("can not load image \n");        return -1;    }    src.copyTo(dst);    for(int row = 1; row<(src.rows - 1); row++)    {        const uchar* previous = src.ptr<uchar>(row - 1);        const uchar* current = src.ptr<uchar>(row);        const uchar* next = src.ptr<uchar>(row + 1);        uchar* output = dst.ptr<uchar>(row);        for(int col = src.channels(); col < (src.cols - 1)*src.channels(); col++)        {            *output = saturate_cast<uchar>(9 * current[col] - 2*previous[col] - 2*next[col] - 2*current[col - src.channels()] - 2*current[col + src.channels()]);            output++;        }    }    namedWindow("image", CV_WINDOW_AUTOSIZE);    imshow("image",dst);    waitKey();    return 0;}

像素重映射

利用cv::remap实现像素重映射；
cv::remap参数说明：

Remap(InputArray src,// 输入图像OutputArray dst,// 输出图像InputArray  map1,// 映射表1（CV_32FC1/CV_32FC2）InputArray map2,// 映射表2（CV_32FC1/CV_32FC2）int interpolation,// 选择的插值int borderMode,// 边界类型（BORDER_CONSTANT）const Scalar borderValue// 颜色 )

插值方法：
CV_INTER_NN =0,
CV_INTER_LINEAR =1,
CV_INTER_CUBIC =2,
CV_INTER_AREA =3,
CV_INTER_LANCZOS4 =4

通过像素重映射实现图像垂直翻转：

#include<opencv2/opencv.hpp>using namespace cv;int main(){    Mat src,dst;    src = imread("E:/image/image/daibola.jpg");    if(src.empty())    {        printf("can not load image \n");        return -1;    }    namedWindow("input", CV_WINDOW_AUTOSIZE);    imshow("input", src);    Mat mapx,mapy;    mapx.create(src.size(), CV_32FC1);    mapy.create(src.size(), CV_32FC1);    for(int row = 0; row < src.rows; row++)    {        for(int col = 0; col < src.cols; col++)        {            mapx.at<float>(row, col) = col;            mapy.at<float>(row, col) = src.rows - row - 1;        }    }    remap(src, dst, mapx, mapy, CV_INTER_NN, BORDER_CONSTANT, Scalar(0,255,255));    namedWindow("output", CV_WINDOW_AUTOSIZE);    imshow("output",dst);    waitKey();    return 0;}