The Core Functionality3(Mask operations on matrices)

增加图像对比度的方法:公式如下,很简单:

The Core Functionality3(Mask operations on matrices)

两个方法:一个是通过遍历图像所有的像素实现,另外一个是同自带库中的掩码函数。

程序如下:

#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>
using namespace std; 
using namespace cv;
static void help(char* progName)
{
    cout << endl
    << "This program shows how to filter images with mask: the write it yourself and the"
    << "filter2d way. " << endl
    << "Usage:" << endl
    << progName << " [image_path -- default ../data/lena.jpg] [G -- grayscale] " << endl << endl;
}
void Sharpen(const Mat& myImage,Mat& Result);
int main( int argc, char* argv[])
{
    help(argv[0]);
    const char* filename = argc >=2 ? argv[1] : "../data/lena.jpg";
    Mat src, dst0, dst1;
    if (argc >= 3 && !strcmp("G", argv[2]))
        src = imread( filename, IMREAD_GRAYSCALE);
    else
        src = imread( filename, IMREAD_COLOR);
       if (src.empty())
        {
            cerr << "Can't open image [" << filename << "]" << endl;
            return -1;
        }
    namedWindow("Input", WINDOW_AUTOSIZE);
    namedWindow("Output", WINDOW_AUTOSIZE);
    imshow( "Input", src );
    double t = (double)getTickCount();
    Sharpen( src, dst0 );
    t = ((double)getTickCount() - t)/getTickFrequency();
    cout << "Hand written function time passed in seconds: " << t << endl;
    imshow( "Output", dst0 );
    waitKey();
    Mat kernel = (Mat_char(3,3) << 0, -1, 0,
    -1, 5, -1,
    0, -1, 0);
    t = (double)getTickCount();
    filter2D( src, dst1, src.depth(), kernel );
    t = ((double)getTickCount() - t)/getTickFrequency();
    cout << "Built-in filter2D time passed in seconds: " << t << endl;
    imshow( "Output", dst1 );
    waitKey();
    return 0;
}
void Sharpen(const Mat& myImage,Mat& Result)
{
   CV_Assert(myImage.depth() == CV_8U); // accept only uchar images
    const int nChannels = myImage.channels();
    Result.create(myImage.size(),myImage.type());
    for(int j = 1 ; j < myImage.rows-1; ++j)
    {
        const uchar* previous = myImage.ptr<uchar>(j - 1);
        const uchar* current = myImage.ptr<uchar>(j );
        const uchar* next = myImage.ptr<uchar>(j + 1);
        uchar* output = Result.ptr<uchar>(j);
        for(int i= nChannels;i < nChannels*(myImage.cols-1); ++i)
        {
            *output++ =saturate_cast(5*current[i]
            -current[i-nChannels] - current[i+nChannels] - previous[i] - next[i]);
        }
    }
    Result.row(0).setTo(Scalar(0));
    Result.row(Result.rows-1).setTo(Scalar(0));
    Result.col(0).setTo(Scalar(0));
    Result.col(Result.cols-1).setTo(Scalar(0));
}

代码写的很清楚,不在解释;掩码操作使用函数:filter2D()

CmakeLists.txt文件!

cmake_minimum_required(VERSION 2.8)
set(CMAKE_CXX_FLAGS "-std=c++11")
project( DisplayImage )
find_package( OpenCV REQUIRED )
include_directories( ${OpenCV_INCLUDE_DIRS} )
add_executable( DisplayImage main.cpp )
target_link_libraries( DisplayImage ${OpenCV_LIBS} )


install(TARGETS DisplayImage RUNTIME DESTINATION bin)

运行和测试结果如下:

The Core Functionality3(Mask operations on matrices)